License Linked Data Resources Pattern
Monika Solanki
Monika Solanki
Stanford University
Stanford University
A GUI for MLN
IMaRS: Incremental Materialization for RDF Streams
Politecnico di Milano
Politecnico di Milano
Akshay Maan
Akshay Maan
Tsinghua University
Tsinghua University
Michael Schuhmacher
Michael Schuhmacher
629560ade61d1839cdc30569839bb4cb105ddf45
Presentation of system 4
Diagrammatic Ontology Patterns
Closing remarks
Chih-Hao Yu
Chih-Hao Yu
114873a9a35bbe14a5a1ccbec176a888c8abd594
Rommel Carvalho
Rommel Carvalho
Bielefeld University
Bielefeld University
Neeraj Koul
Neeraj Koul
Other Stream Reasoning approaches
David R. Karger
David R. Karger
Terminology-Based Patterns for Natural Language Definitions in Ontologies
CrowdSem Welcome and introduction
Presentation of system 3
LORIA
LORIA
Henri Bal
Henri Bal
fd8c8c753f52640dd96a10d417c345e6ea333841
Samantha Bail
Samantha Bail
3eb298593f1ca8d13b94206d401d01555ffa2e89
Queensland University of Technology
Queensland University of Technology
Michele Catasta
Michele Catasta
d99a1fc99c3993b971415dd553bac86360582207
Wrap-up and conclusions
North Carolina State University
North Carolina State University
Roberto Navigli
Roberto Navigli
e1022bd143e97df8ee468e081697d285db7be442
Jacopo Urbani
Jacopo Urbani
adee22b352dd8781301e45e715855e4d92dc034b
Design of the crowdsourcing exercise
University of Applied Sciences and Arts Western Switzerland
University of Applied Sciences and Arts Western Switzerland
Presentation of system 2
Peter Mork
Peter Mork
Pontifical Catholic University of Chile
Pontifical Catholic University of Chile
Monash University
Monash University
Sabine Sachweh
Sabine Sachweh
Dr. Detective: combining gamification techniques and crowdsourcing to create a gold standard in medical text
Presentation of system 1
University of Liverpool
University of Liverpool
Ken Laskey
Ken Laskey
Mahsa Chitsaz
Mahsa Chitsaz
David Ratcliffe
David Ratcliffe
University of Western Sydney
University of Western Sydney
Introduction to the OAEI 2013 campaign
Holger Wache
Holger Wache
Nicolas Matentzoglu
Nicolas Matentzoglu
8bfb88288cdf2930fac4c97945b88d52fec277bc
431b24d294c0a75a1001a0f34b32815c2ec61fed
Query Suggestion by Concept Instantiation
Query Suggestion by Concept Instantiation
A class of search queries which contain abstract concepts are studied in this paper. These queries cannot be correctly interpreted by traditional keyword-based search engines. This paper presents a simple framework that detects and instantiates the abstract concepts by their concrete entities or meanings to produce alternate queries that yield better search results.
Industrial Track
MODUL University Vienna
MODUL University Vienna
Kirk A. Ogaard
Kirk A. Ogaard
AIFB, University of Karlsruhe
AIFB, University of Karlsruhe
Data Management & Exploration
Curating Semantic Linked Open Datasets for Software Engineering
Curating Semantic Linked Open Datasets for Software Engineering
A typical software engineer spends a significant amount of time and effort reading technical manuals to find answers to questions especially those related to features, versions, compatibilities and dependencies of software and hardware components, languages, standards, modules, libraries and products. It is currently not possible to provide a semantic solution to their problem primarily due to the non-availability of comprehensive semantic datasets in the domains of information technology. In this work, we have extracted, integrated and curated a linked open dataset (LOD) called LOaD-IT exclusively on this domain from a variety of sources including other LODs such as Freebase and DBPedia, technical documentation such as JavaDocs and others. Further, we have built a technical helpdesk system using a semantic query engine that derives answers from LOaD-IT. Our system demonstrates how productivity of the software engineer can be improved by eliminating the need to read through lengthy technical manuals. We expect LOaD-IT to become more comprehensive in the future and to find other related practical applications.
Tomi Kauppinen
Tomi Kauppinen
Alejandro Fernández-Carrera
Alejandro Fernández-Carrera
Chris Baillie
Chris Baillie
6fb5a96a446e73369ffeff680a10a3988cdd3778
Massachusetts General Hospital
Massachusetts General Hospital
Thomas Scharrenbach
Thomas Scharrenbach
4f445317b3d8083b33108e0cd74277e5569af62d
Samsung Information Systems America
Samsung Information Systems America
Evan Patton
Evan Patton
e2f988aab30d55fb07e05a08d3d376a708158e4c
W3C
W3C
RelClus: Clustering-based Relationship Search
RelClus: Clustering-based Relationship Search
Searching and browsing relationships between entities is an important task in many domains. To support users in interactively exploring a large set of relationships, we present a novel relationship search engine called RelClus, which automatically groups search results into a dynamically generated hierarchy with meaningful labels. This hierarchical clustering of relationships exploits their schematic patterns and a similarity measure based on information theory.
SPARQL
Sören Auer
Sören Auer
09ac456515dee0896e8eba4b06ae589bef2069cf
Nigel Shadbolt
Nigel Shadbolt
Content-Preserving Graphics
Enterprise Linked Data
URSW 2013 Session 1
Zhichun Wang
Zhichun Wang
45451c79be088fbccc5319ac32a843c8c94e8314
DiTTO: Diagrams Transformation inTo OWL
DiTTO: Diagrams Transformation inTo OWL
In this paper we introduce DiTTO, an online service that allows one to convert a E/R diagram created through the yEd diagram editor into a proper OWL ontology according to three different conversion strategies.
Hassan Aït-Kaci
Hassan Aït-Kaci
ba78b21edcd0aef11e674885e8303c17f4bd1ebc
Linked Data Platform as a novel approach for Enterprise Application Integration
Bounds: Expressing Reservations about Incoming Data
URSW 2013 Session 2
Nathalie Hernandez
Nathalie Hernandez
a415f377a8de5a234d39501779e6e383333370ab
Optique 1.0: Semantic Access to Big Data; The Case of Norwegian Petroleum Directorate’s FactPages
Optique 1.0: Semantic Access to Big Data; The Case of Norwegian Petroleum Directorate’s FactPages
The Optique project aims at developing an end-to-end system for semantic data access to Big Data in industries such as Statoil ASA and Siemens AG. In our demonstration we present the first version of the Optique system customised for the Norwegian Petroleum Directorate's FactPages, a public data available for engineers at Statoil ASA. The system provides different options, including visual, to formulate queries over ontologies and to display query answers. Optique~1.0 offers two installation wizards that allow to extract ontologies from relational schemas, extract and define mappings connecting ontologies and schemas, and align and approximate ontologies. Moreover, the system offers tools to edit these components and highly optimised techniques for query answering.
Keio University
Keio University
Hunting for Inconsistencies in Multilingual DBpedia with QAKiS
Hunting for Inconsistencies in Multilingual DBpedia with QAKiS
QAKiS, a system for open domain Question Answering over linked data, allows to query DBpedia multilingual chapters with natural language questions. But since such chapters can contain different information w.r.t. the English version (e.g. more specificity on certain topics, or fill information gaps), i) different results can be obtained for the same query, and ii) the combination of these query results may lead to inconsistent information about the same topic. To reconcile information obtainedby distributed SPARQL endpoints, an argumentation-based module is integrated into QAKiS to reason over inconsistent information sets, and to provide a unique and motivated answer to the user.
LRIMM
LRIMM
IIIT Delhi
IIIT Delhi
University of Oxford
University of Oxford
Consuming Linked data in Supply Chains: Enabling data visibility via Linked Pedigrees
Lora Aroyo
Lora Aroyo
Maxine Kruijt
Maxine Kruijt
Closing Ceremony
Mun Yi
Mun Yi
07226d42ae620a8c423c5846e4e8da7bf358aace
Elena Cabrio
Elena Cabrio
346975d5d464d0d7523593d6bef915a11ff219c4
A Protein Annotation Framework Empowered with Semantic Reasoning
A Protein Annotation Framework Empowered with Semantic Reasoning
This paper presents an association discovery framework for proteins based on semantic annotations from biomedical literature. An automatic ontology-based annotation method is used to create a semantic protein annotation knowledge base. A semantic reasoning service enables realisation reasoning on original annotations to infer more accurate associations and executes semantic query transformation. A case study on protein-disease association discovery on a real-world colorectal cancer dataset is presented.
Raúl García-Castro
Raúl García-Castro
Prateek Jain
Prateek Jain
Dmitriy Zheleznyakov
Dmitriy Zheleznyakov
ae369e4d41a81ab112ac21fe44b96510e4ff7f7c
Rochelle Dacuycuy-Pacio
Rochelle Dacuycuy-Pacio
Demo: Swip, a Semantic Web Interface using Patterns
Demo: Swip, a Semantic Web Interface using Patterns
Our purpose is to provide end-users a means to query ontology based knowledge bases using natural language queries and thus hide the complexity of formulating a query expressed in a graph query language such as SPARQL. The main originality of our approach lies in the use of query patterns. Our contribution is materialized in a system named SWIP, standing for Semantic Web Interface Using Patterns. The demo will present use cases of this system.
Viktoria Pammer
Viktoria Pammer
University of Brighton
University of Brighton
Pleasantly Consuming Linked Data with RDF Data Descriptions
Andriy Nikolov
Andriy Nikolov
8bd5b6c3bdb42bf83ff88fa78077df7e75649eb0
Delft University of Technology
Delft University of Technology
Konstantina Bereta
Konstantina Bereta
6dc2e6c44ba12728237ec901f3f5190970a8dbf3
Irene Celino
Irene Celino
Closing and best poster award
Yujiao Zhou
Yujiao Zhou
Spyros Kotoulas
Spyros Kotoulas
e879e287903caecdd41354eb5ae7aff6d9bc741b
Denoting Data in the Grounded Annotation Framework
Denoting Data in the Grounded Annotation Framework
Semantic web applications are integrating data from more and more different types of sources about events. However, most data annotation frameworks do not translate well to semantic web. We present the grounded annotation framework (GAF), a two-layered framework that aims to build a bridge between mentions of events in a data source such as a text document and their formal representation as instance}. By choosing a two-layered approach, neither the mention layer, nor the semantic layer needs to compromise on what can be represented. We demonstrate the strengths of GAF in flexibility and reasoning through a use case on earthquakes in Southeast Asia.
Ghislain Auguste Atemezing
Ghislain Auguste Atemezing
Kewen Wang
Kewen Wang
University of Nottingham
University of Nottingham
Poster session (Patterns and short papers)
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/-
Joao Leite
Joao Leite
e2193aee720664440d8506adba42199f2a4bed6a
National Insititute of Advanced Industrial Science and Technology (Japan)
National Insititute of Advanced Industrial Science and Technology (Japan)
Amit Sheth
Amit Sheth
Yahoo! Research
Yahoo! Research
Sofia Pinto
Sofia Pinto
Abstracting Transport to an Ontology Design Pattern for the Geosciences
UMP-ST plug-in: a tool for documenting, maintaing, and evolving probabilistic ontologies
Linked Data for Financial Reporting
TBD
Thomas Erickson
Thomas Erickson
0a8e71602833f08471e6ca922c16c3fd57ecd6e9
Olga Krebs
Olga Krebs
The Object with States Ontology Design Pattern
Rights declaration in Linked Data
Reliability Analyses of Open Government Data
Alexandre Passant
Alexandre Passant
W3C Australia
W3C Australia
Marina Gueroussova
Marina Gueroussova
Opening and welcome
The Event Processing ODP
A snapshot of the OWL Web
Yuan-Fang Li
Yuan-Fang Li
f1286b01c0c51c46b55258088fc54824d6b86bf1
Kieron O'Hara
Kieron O'Hara
Pierre van de Laar
Pierre van de Laar
Towards a Configurable Framework for Iterative Signing of Distributed Graph Data
Riccardo Rosati
Riccardo Rosati
347c5f7b49d6802f343668845c30c5e610d28a7f
Fengyu Yang
Fengyu Yang
d9fc57211695f662cefb48f984f16c01aeceaec2
Deployment of RDFa, Microdata, and Microformats on the Web – A Quantitative Analysis
Egor V. Kostylev
Egor V. Kostylev
35802170b5b15f757b117328a0108900b72b0fee
Mathieu D'Aquin
Mathieu D'Aquin
e61cc68181adeb9fbbddc539a6fa01dd24b299c8
Simon Castillo
Simon Castillo
39007594cf78c0c951c723ef8c20067639d1c96d
Poznań University of Economics
Poznań University of Economics
Marcelo Ladeira
Marcelo Ladeira
David Damen
David Damen
Energy efficient sensing for managing privacy on smartphones
Argus Labs
Argus Labs
Alessandro Margara
Alessandro Margara
276c86b789de1aa807a1923432b540b646821ba2
OM-2013 Afternoon Tea / Poster session
When History Matters - Assessing Reliability for the Reuse of Scientific Workflows
Samsung Electronics
Samsung Electronics
Jeff Z. Pan
Jeff Z. Pan
Olga Zhibrik
Olga Zhibrik
a04077d64fda06662bf90d5a21d9250c7ce868a4
Brett Cooke
Brett Cooke
3d05b566c17337f889987a6d5b98fcbf0dffc313
Simplified OWL Ontology Editing for the Web: Is WebProtégé Enough?
Tomáš Kliegr
Tomáš Kliegr
OM-2013 Session 3 (OAEI-2013)
Hanmin Jung
Hanmin Jung
Andre Freitas
Andre Freitas
d3b73e11f371a9fee2e23ec599408f5ca4ecdfe9
Indira Yerramareddy
Indira Yerramareddy
Min-Joong Lee
Min-Joong Lee
265f2aedc53fcc0d45ca2a841a6a3e4728a7f220
Michel Dumontier
Michel Dumontier
Christoph Einsiedler
Christoph Einsiedler
f97c9e5d3c2d3ad45e7fda23163a4ab8ecd15f84
Raphaël Troncy
Raphaël Troncy
Michael Uschold
Michael Uschold
Abraham Bernstein
Abraham Bernstein
8704ad77580618cb845036d3a15626d30fd828c3
Andreas Kasten
Andreas Kasten
Iacopo Vagliano
Iacopo Vagliano
1a99c8343fad8896b37558f20b17153b18f5611a
KMi, The Open University
KMi, The Open University
Michael Compton
Michael Compton
8a03fee583ab9055491b1bb1f9996a498b360144
Steven Lynden
Steven Lynden
49b44a6ef0e7a2fb94bd264d434a5775461f1245
Semantic Big Data in Australia - from Dingoes to Drysdale
University of Aberdeen
University of Aberdeen
A Min Tjoa
A Min Tjoa
Michael Ovelgönne
Michael Ovelgönne
5fb6c430ba06cabc2e0c9dd6c83c2c4bdf54225c
P.E.S. Institute of Technology
P.E.S. Institute of Technology
Towards an RDF Analytics Language: Learning from Successful Experiences
Thanh Tran
Thanh Tran
13a8957f89cffa9ca37a4525e19792bd3ba8ca54
David De Roure
David De Roure
Poster and Demo Track
Caroline Barrière
Caroline Barrière
University of Leeds
University of Leeds
Semantic Web Technologies for Social Translucence and Privacy Mirrors on the Web
Progress in Open-World, Integrative, Transparent, Collaborative Science Data Platforms
Graße—Towards Flexible Search on Encrypted Graph Data
University of New South Wales
University of New South Wales
Detecting and Reporting Extensional Concept Drift in Statistical Linked Data
Detecting and Reporting Extensional Concept Drift in Statistical Linked Data
Knarig Arabshian
Knarig Arabshian
Personal Privacy and the Web of Linked Data
Jérôme Euzenat
Jérôme Euzenat
Shubham Gupta
Shubham Gupta
c9815062fd77450e1054f6a58ce350de00046a23
eBay
eBay
Light at the End of the Tunnel
Ulrike Sattler
Ulrike Sattler
Miriam Fernandez
Miriam Fernandez
bf9aae3c7b2fc98e26382c4d558508d885a3850f
Manos Karpathiotakis
Manos Karpathiotakis
789ce1bf376c1f816664b3d77f81d73eea21a618
Logic 1
Marco Fossati
Marco Fossati
Jonathan Yu
Jonathan Yu
Henrique Da Rocha
Henrique Da Rocha
Craig A. Knoblock
Craig A. Knoblock
Complex correspondences for query patterns rewriting
Complex correspondences for query patterns rewriting
Christian Y. A. Brenninkmeijer
Christian Y. A. Brenninkmeijer
Multilingual Semantics
Duke University
Duke University
Antonino Rotolo
Antonino Rotolo
10bb824c115fec3099eb469c8939a89518f14fac
Melisachew Wudage Chekol
Melisachew Wudage Chekol
795f113ba89d73d202c0f85b54b33d95673d9038
Semantic Web Challenge 1
IRIT
IRIT
Daniel Gerber
Daniel Gerber
7716ea9608422625fa7ba043975f357ef856060f
Juanzi Li
Juanzi Li
2abc14d49e48dc06033e689f1ff347a0c94452fa
To repair or not to repair: reconciling correctness and coherence in ontology reference alignments
To repair or not to repair: reconciling correctness and coherence in ontology reference alignments
BBC Research & Development
BBC Research & Development
Silvio Peroni
Silvio Peroni
bae1bc13f570dff4f084b1c9b95ed97c9d5acbf0
Cristian Confalonieri
Cristian Confalonieri
c8196b5bd222783a5135238d5db7880432ef4c01
Carleton University
Carleton University
Heiner Stuckenschmidt
Heiner Stuckenschmidt
f072571d8c8abd21e637a9dec2c5e835165c8ece
Vulcan Inc.
Vulcan Inc.
Rapid execution of weighted edit distances
Rapid execution of weighted edit distances
National Library of Medicine
National Library of Medicine
Ceriel Jacobs
Ceriel Jacobs
6f2ec7e73bdf1d276fead72dca422caae9c0009b
Towards Constructive Evidence of Data Flow-oriented Web Service Composition
Michele Barbera
Michele Barbera
IncMap: pay as you go matching of relational schemata to OWL ontologies
IncMap: pay as you go matching of relational schemata to OWL ontologies
Carlos Castillo
Carlos Castillo
Mary-Anne Williams
Mary-Anne Williams
Arild Waaler
Arild Waaler
ff749127c207b8bc7d463999eea7531e0d7d9aba
Kai Holzweißig
Kai Holzweißig
A Query Tool for EL with Non-monotonic rules
CEFRIEL
CEFRIEL
Unsupervised learning of link specifications: deterministic vs. non-deterministic
Unsupervised learning of link specifications: deterministic vs. non-deterministic
On the Status of Experimental Research on the Semantic Web
Michael Schmidt
Michael Schmidt
92f314774e71485a0f35688d78278e18ad1b8489
Harry Halpin
Harry Halpin
LinkedIn
LinkedIn
Marco Console
Marco Console
1af9f1873abe4815d7a221e6fad909058b08cc91
Harith Alani
Harith Alani
ad0c7d68490b84d6c7f8b0cb8aa1e457559386ef
Semafor Systems
Semafor Systems
Peter Patel-Schneider
Peter Patel-Schneider
35a838a13f014e0d3924f7a0aeeb929105fbf234
SPARQL Update under RDFS Entailment in Fully Materialized and Redundancy-Free Triple Stores
Robert-Jan Sips
Robert-Jan Sips
On the need for a W3C community group on RDF Stream Processing
WaSABi: Workshop on Semantic Web Enterprise Adoption and Best Practice
Rafael S. Gonçalves
Rafael S. Gonçalves
051af5c11e8f64bc668957e15b9a3ea541a386b2
Jason Ellis
Jason Ellis
e1b2880c987f70e7be1096bc9672bbb93db12e4b
Michael Gruninger
Michael Gruninger
Estevão Aguiar
Estevão Aguiar
Heidelberg Institute for Theoretical Studies
Heidelberg Institute for Theoretical Studies
Frank Van Harmelen
Frank Van Harmelen
61c8d2dcc50fab61e7f66101bd4d063d8ab4124d
BBC
BBC
Kathryn Laskey
Kathryn Laskey
Extending SPARQL with Qualitative Preferences
Cornelius Kloppers
Cornelius Kloppers
Sebastian Tramp
Sebastian Tramp
Towards a Vocabulary for Incorporating Predictive Models into the Linked Data Web
Towards a Vocabulary for Incorporating Predictive Models into the Linked Data Web
Jason Jung
Jason Jung
Jose Manuel Gomez-Perez
Jose Manuel Gomez-Perez
d95c6613086420712f5f0e79533ec46223c4ae93
Order Theoretical Semantic Recommendation
Aleix Garrido
Aleix Garrido
c78cbf7d1fd965923c3f81573a73d8b581e38b10
Olivier Teste
Olivier Teste
CMU
CMU
Riichiro Mizoguchi
Riichiro Mizoguchi
3rd International Workshop on Linked Science 2013
Leigh Dodds
Leigh Dodds
Gerd Stumme
Gerd Stumme
Vasant Honavar
Vasant Honavar
Nikita Zhiltsov
Nikita Zhiltsov
e1b592dfb8c017c986d0b3937db26d33120b9ef4
4th International Workshop on Consuming Linked Data
Sapienza University of Rome
Sapienza University of Rome
ORCHID – Reduction-Ratio-Optimal Computation of Geo-Spatial Distances for Link Discovery
Hak-Lae Kim
Hak-Lae Kim
Juan Bello
Juan Bello
Camille Pradel
Camille Pradel
ef03f638ac5d3105c4051d4796d08c99dd32881b
Introduction: Order Matters!
Semantic Arts, Inc.
Semantic Arts, Inc.
Self-Sustaining Platforms: a Semantic Workflow Engine
Luke Mondor
Luke Mondor
c74844a5d84888c3ca6cb1106af1ec2903292bfe
Geographica: A Benchmark for Geospatial RDF Stores
47df72dfef38eb3cd02cb6259bb46bcb5f5c55f3
Pascal Hitzler
Pascal Hitzler
d9d5e01de07e6f9a5e8b66c44c995c5ca8cc3b63
Technical University Munich
Technical University Munich
Jesse Jiaxin Wang
Jesse Jiaxin Wang
Bo Hu
Bo Hu
NECTEC
NECTEC
Change-a-LOD: Does the Schema on the Linked Data Cloud Change or Not?
Charith Perera
Charith Perera
b1fa0aa2e148b08ed2f470fbe8902e8e486f612e
EURECOM
EURECOM
Khoa Nguyen
Khoa Nguyen
Yves Raimond
Yves Raimond
c99a220cc2b8dacc4d4de0342a3909c73eb4e2be
On-the-fly Integration of Static and Dynamic Linked Data
Areti Karamanou
Areti Karamanou
University of Southern California
University of Southern California
Luigi Sauro
Luigi Sauro
0f07e2976fe6dfef5dc5cc9693549021b54f6e76
Martin Peters
Martin Peters
Geert-Jan Houben
Geert-Jan Houben
The Energy Management Adviser at EDF
The Energy Management Adviser at EDF
The EMA (Energy Management Adviser) aims to produce personalised energy saving advice for EDF’s customers. The advice takes the form of one or more ‘tips’, and personalisation is achieved using semantic technologies: customers are described using RDF, an OWL ontology provides a conceptual model of the relevant domain (housing, environment, and so on) and the different kinds of tips, and SPARQL query answering is used to identify relevant tips. The current prototype provides tips to more than 300,000 EDF customers in France at least twice a year. The main challenges for our future work include providing a timely service for all of the 35 million EDF customers in France, simplifying the system’s maintenance, and providing new ways for interacting with customers such as via a Web site.
Including Co-referent URIs in a SPARQL Query
Mark Schildhauer
Mark Schildhauer
National and Kapodistrian University of Athens
National and Kapodistrian University of Athens
Pilsik Choi
Pilsik Choi
456ddde8a301f3c6fd06bff841a242ba620b65b0
Natural Language Query Translation into SPARQL using Patterns
Incorporating Commercial and Private Data into an Open Linked Data Platform for Drug Discovery
Incorporating Commercial and Private Data into an Open Linked Data Platform for Drug Discovery
The Open PHACTS Discovery Platform aims to provide an integrated information space to advance pharmacological research in the area of drug discovery. Effective drug discovery requires comprehensive data coverage, i.e. integrating all available sources of pharmacology data. While many relevant data sources are available on the linked open data cloud, their content needs to be combined with that of commercial datasets and the licensing of these commercial datasets respected when providing access to the data. Additionally, pharmaceutical companies have built up their own extensive private data collections that they require to be included in their pharmacological dataspace. In this paper we discuss the challenges of incorporating private and commercial data into a linked dataspace: focusing on the modelling of these datasets and their interlinking. We also present the graph-based access control mechanism that ensures commercial and private datasets are only available to authorized users.
Luca Foschini
Luca Foschini
fe6cf07e71d492e282fc70604c7c6a9821b10216
Kostis Kyzirakos
Kostis Kyzirakos
a45138009890ce780bd31806e8888b8a2f26d1af
8th International Workshop on Ontology Matching
Deployment of RDFa, Microdata, and Microformats on the Web – A Quantitative Analysis
Deployment of RDFa, Microdata, and Microformats on the Web – A Quantitative Analysis
More and more websites embed structured data describing for instance products, reviews, blog posts, people, organizations, events, and cooking recipes into their HTML pages using markup standards such as Microformats, Microdata and RDFa. This development has accelerated in the last two years as major Web companies, such as Google, Facebook, Yahoo!, and Microsoft, have started to use the embedded data within their applications. In this paper, we analyze the adoption of RDFa, Microdata, and Microformats across the Web. Our study is based on a large public Web crawl dating from early 2012 and consisting of 3 billion HTML pages which originate from over 40 million websites. The analysis reveals the deployment of the different markup standards, the main topical areas of the published data as well as the different vocabularies that are used within each topical area to represent data. What distinguishes our work from earlier studies, published by the large Web companies, is that the analyzed crawl as well as the extracted data are publicly available. This allows our findings to be verified and to be used as starting points for further domain-specific investigations as well as for focused information extraction endeavors.
Padmashree Ravindra
Padmashree Ravindra
Marco Balduini
Marco Balduini
cfab487eaef36c19086e0179c2fe26284f2d913a
1ddf92412fb64e39b877b6d8429552e62009f8cc
Victoria Uren
Victoria Uren
Maxine Sherrin
Maxine Sherrin
Wolfgang Mueller
Wolfgang Mueller
233528af3d75389bb1a4b1087324f95522773bc2
Xavier Serra
Xavier Serra
Entity recommendations in Web Search
Entity recommendations in Web Search
While some web search users know exactly what they are looking for, others are willing to explore topics related to an initial interest. Often, the user’s initial interest can be uniquely linked to an entity in a knowledge base. In this case, it is natural to recommend the explicitly linked entities for further exploration. In real world knowledge bases, however, the number of linked entities may be very large and not all related entities may be equally relevant. Thus, there is a need for ranking related entities. In this paper, we describe Spark, a recommendation engine that links a user’s initial query to an entity within a knowledge base and provides a ranking of the related entities. Spark extracts several signals from a variety of data sources, including Yahoo! Web Search, Twitter, and Flickr, using a large cluster of computers running Hadoop. These signals are combined with a machine learned ranking model in order to produce a final recommendation of entities to user queries. This system is currently powering Yahoo! Web Search result pages.
Cameron Mclean
Cameron Mclean
Marie-Aude Aufaure
Marie-Aude Aufaure
DERI, Galway
DERI, Galway
Carsten Lutz
Carsten Lutz
94c551711a91bc94a68e35dd5c388d0c58df7095
Georgi Georgiev
Georgi Georgiev
Daniel P. Miranker
Daniel P. Miranker
Centrum Wiskunde & Informatica
Centrum Wiskunde & Informatica
Víctor Rodríguez-Doncel
Víctor Rodríguez-Doncel
Julien Cojan
Julien Cojan
07189fb430e72e892b2278998e4cc698da8b96c0
Line C. Pouchard
Line C. Pouchard
Héctor Pérez-Urbina
Héctor Pérez-Urbina
Fouad Zablith
Fouad Zablith
University of Surrey
University of Surrey
Sever Fundatureanu
Sever Fundatureanu
b37ff209df93fbe699d8640b4befd01f7ea9392e
Christian Hütter
Christian Hütter
4ae9a516a209cfdbaa995eecbed5835e0f23ee8b
Luiz André P. Paes Leme
Luiz André P. Paes Leme
c61e7c944f2fc1586ba1acf727471b1c9435b1d2
Czech Technical University in Prague
Czech Technical University in Prague
Social listening of City Scale Events using the Streaming Linked Data Framework
Social listening of City Scale Events using the Streaming Linked Data Framework
City-scale events may easily attract half a million of visitors in hundreds of venues over just a few days. Which are the most attended venues? What do visitors think about them? How do they feel before, during and after the event? These are few of the questions a city-scale event manger would like to see answered in real-time. In this paper, we report on our experience in social listening of two city-scale events (London Olympic Games 2012, and Milano Design Week 2013) using the Streaming Linked Data Framework.
Anila Sahar Butt
Anila Sahar Butt
3aacab1124756694855de36f785fa33fec847229
iSOCO, S.A.
iSOCO, S.A.
Mark Musen
Mark Musen
60602b405f9d456ffc0e30d22d535100159b7874
Ian Horrocks
Ian Horrocks
3361a8a2f71036d7ca03076a41f4d8ae08c71e97
1b2b8ccf3aa13a2046ddda3496c815078774aca9
Marco Ruzzi
Marco Ruzzi
78157ae6c233202f8c1bf40809b6843c3f6af793
Exploiting Stream Reasoning to Monitor multi-Cloud Applications
Thomas Hornung
Thomas Hornung
72ed92ade9e589dcf8c52b51216a65b8b7fe01ac
University of Toronto
University of Toronto
Martin Grund
Martin Grund
273314f02e548c9fd13e40aed8684be958cfa948
Chris Bizer
Chris Bizer
Southeast University
Southeast University
Choosing Between Graph Databases and RDF Engines for Consuming and Mining Linked Data
Choosing Between Graph Databases and RDF Engines for Consuming and Mining Linked Data
Giorgos Stoilos
Giorgos Stoilos
Assessing Content Value for Digital Publishing through Relevance and Provenance-based Trust
Olivier Bodenreider
Olivier Bodenreider
Csongor I Nyulas
Csongor I Nyulas
88bb713ff705a7fe7262fda87b705b31118e76b8
Kavitha Srinivas
Kavitha Srinivas
3524dd31de79a544b21dd104327c3c7eb9a9f139
wrap-up
Dbpedia & NLP 2013 Session 3
Using BabelNet in Bridging the Gap Between Natural Language Queries and Linked Data Concepts
Using BabelNet in Bridging the Gap Between Natural Language Queries and Linked Data Concepts
Utilising Provenance to Enhance Social Computation
Crowdsourcing Ontology Verification
Stijn Verstichel
Stijn Verstichel
de9818189d67a0849e2863a93603fbb903be788f
Wei Jia Shen
Wei Jia Shen
7418db7e9cad17a54c76e632c6d8721a73c3b06b
Benjamin Zapilko
Benjamin Zapilko
COLD 2013 Session 3
David Henry
David Henry
Peter Davis
Peter Davis
COLD 2013 Session 4
Christian Dinu
Christian Dinu
cd6af0d194cddeb81780252586996ae24fe8cbaf
DBpedia & NLP 2013 Session 2
DBpediaNYD A Silver Standard Benchmark Dataset for Semantic Relatedness in Dbpedia
DBpediaNYD A Silver Standard Benchmark Dataset for Semantic Relatedness in Dbpedia
Including Co-referent URIs in a SPARQL Query
Including Co-referent URIs in a SPARQL Query
Wei Hu
Wei Hu
Big Data meets Big Social: Social Machines and the Semantic Web
Optimizing RDF stores by coupling General-purpose Graphics Processing Units and Central Processing Units
Pleasantly Consuming Linked Data with RDF Data Descriptions
Pleasantly Consuming Linked Data with RDF Data Descriptions
Ricardo Usbeck
Ricardo Usbeck
ebf2fa4fd6d3c314b787313582e2cb0deb7829ae
Dbpedia & NLP 2013 Session 1
Towards Linked Data based Enterprise Information Integration
Towards Linked Data based Enterprise Information Integration
Extending the Coverage of DBpedia Properties using Distant Supervision over Wikipedia
Extending the Coverage of DBpedia Properties using Distant Supervision over Wikipedia
OM-2013 Session 1
Andreas Harth
Andreas Harth
Bounds: Expressing Reservations about Incoming Data
Bounds: Expressing Reservations about Incoming Data
OM-2013 Paper presentation session 2
Nandana Mihindukulasooriya
Nandana Mihindukulasooriya
Inanc Seylan
Inanc Seylan
95830903bfd33adae4c4f013080170bcebd5f9d6
Boosting RDF Adoption in Ruby with Goo
Christopher Brewster
Christopher Brewster
A lemon lexicon for DBpedia
A lemon lexicon for DBpedia
Gregory Falzon
Gregory Falzon
a6bcbadf597532c70b1ccf7f99a7d884c4c80731
On Managing Prefixes of LOD Vocabularies
On Managing Prefixes of LOD Vocabularies
Semantic Web In use Track
Brandon Whitehead
Brandon Whitehead
On Managing Prefixes of LOD Vocabularies
Mike Dean
Mike Dean
Norwegian University of Science and Technology
Norwegian University of Science and Technology
Naive reasoning on RDF streams
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems
Isabelle Augenstein
Isabelle Augenstein
27827e5e1e283e3c10a409d2fb75d72754510e5c
Adaptive Semantic Publishing
Adaptive Semantic Publishing
Son Bao Pham
Son Bao Pham
2da4622eb4ec2c318910a72fe9ed17048a80bf3a
Dagmar Gromann
Dagmar Gromann
Neel Guha
Neel Guha
Brainstorm
Anna Lisa Gentile
375c571224d2571a38961ee728085ac27d28f094
Anna Lisa
Gentile
Anna Lisa Gentile
Anna Lisa Gentile
Max Planck Institute for Computer Science
Max Planck Institute for Computer Science
Kerry Taylor
Kerry Taylor
404235450b5723d80a4a9d89df7c7166624c229a
University of Pennsylvania
University of Pennsylvania
RDF stream processing models
COLD 2013 Session 2
From Strings to Things SAR-Graphs: A New Type of Resource for Connecting Knowledge and Language
From Strings to Things SAR-Graphs: A New Type of Resource for Connecting Knowledge and Language
A user interface to build interactive visualizations for the semantic web
A user interface to build interactive visualizations for the semantic web
While the web of linked data gets increasingly richer in size and complexity, its use is still constrained by the lack of applications consuming this data. We propose a Web-based tool to build and execute complex applications to transform, integrate and visualize Semantic Web data. Applications are composed as pipelines of a few basic components and completely based on Semantic Web standards, including SPARQL Construct for data transformation and SPARQL Update for state transition. The main novelty of the approach lays in the support to interaction, through the availability of user interface event streams as pipeline inputs.
Espen H. Lian
Espen H. Lian
35ef921c9310f361d41c41d96c00e729ac7fda0f
Natural Language Query Translation into SPARQL using Patterns
Natural Language Query Translation into SPARQL using Patterns
Explaining data patterns using background knowledge from Linked Data
Piek Vossen
Piek Vossen
2fb5ed1f5e4cfdbbdb384e1e0b841a07569ede92
TBA
Edmond Jajaga
Edmond Jajaga
WebMediaBrands
WebMediaBrands
Aibo Tian
Aibo Tian
8e6e08bd78f610033fcb23b4004d6022fe158a1b
COLD 2013 Session 1
Terry Payne
Terry Payne
University of Passau
University of Passau
Stream Reasoning introduction
Peter Haase
Peter Haase
fec12b76b11eceb8dce87a648d055583e575d0c6
Alexander Arturo Mera Caraballo
Alexander Arturo Mera Caraballo
82a673fa35a6624e57c522f09cc7ed02de3edb29
Sebastian Ewert
Sebastian Ewert
Dbpedia & NLP 2013 Session 4
Coordinating Social Care and Healthcare using Semantic Web Technologies
Coordinating Social Care and Healthcare using Semantic Web Technologies
Social care and Healthcare are unique in terms of cultural importance, economic size and domain complexity. Combining information systems from both domains poses unique scientific and technical challenges with regard to information representation, access, integration and retrieval granularity. We present a semantics-based approach that is uniquely positioned to access information across domains using a combination of business rules and contextual exploration. A proof of concept illustrates that semantic technologies can cope in a scenario where traditional data integration approaches are too costly and reduce the addressable information space.
Argumentation-based Inconsistencies Detection for Question-Answering over DBpedia
Argumentation-based Inconsistencies Detection for Question-Answering over DBpedia
Boosting RDF Adoption in Ruby with Goo
Boosting RDF Adoption in Ruby with Goo
Interactive Pay as you go Relational-to-Ontology Mapping
On-the-fly Integration of Static and Dynamic Linked Data
On-the-fly Integration of Static and Dynamic Linked Data
CNR
CNR
Tomas Vitvar
Tomas Vitvar
XKOS: Extending SKOS for Describing Statistical Classifications
XKOS: Extending SKOS for Describing Statistical Classifications
Richard Rawnsley
Richard Rawnsley
The Benefits of Incremental Reasoning in OWL EL
The Benefits of Incremental Reasoning in OWL EL
This demo will present the advantages of the new, bookkeeping-free method for incremental reasoning in OWL EL on incremental classification of large ontologies. In particular, we will show how a typical experience of a user editing a large ontology can be improved if the reasoner (or ontology IDE) provides the capability of instantaneously re-classifying the ontology in the background mode when a change is made. In addition, we intend to demonstrate how incremental reasoning helps in other tasks such as answering DL queries and computing explanations of entailments. We will use our OWL EL reasoner ELK and its Protege plug-in as the main tools to highlight these benefits.
Jin Ha Lee
Jin Ha Lee
Matthew Rowe
Matthew Rowe
Hui Miao
Hui Miao
35cf1690fd26511f4f39e4a72961d7881ce44f60
Peter Eklund
Peter Eklund
David Bainbridge
David Bainbridge
Haofen Wang
Haofen Wang
Towards Easy Matching Between Statistical Linked Data: Dimension Patterns
Towards Easy Matching Between Statistical Linked Data: Dimension Patterns
Marco Rospocher
Marco Rospocher
Bernard Vatant
Bernard Vatant
Michael Zakharyaschev
Michael Zakharyaschev
Klaus Berberich
Klaus Berberich
b5e2697f7c9877ed37b9f9b32ed6b08d3a40c4ee
Sean O'Riain
Sean O'Riain
Roman Kontchakov
Roman Kontchakov
Australian Bureau of Statistics Implementation of Semantic Web Technology
Australian Bureau of Statistics Implementation of Semantic Web Technology
AnHai Doan
AnHai Doan
Alexander Krumpholz
Alexander Krumpholz
Logic 2
Extending DBpedia with Wikipedia List Pages
Extending DBpedia with Wikipedia List Pages
Anja Jentzsch
Anja Jentzsch
Lule Ahmedi
Lule Ahmedi
NICTA
NICTA
Towards the Discovery of Person-Level Data - Reuse of Vocabularies and Related Use Cases
Towards the Discovery of Person-Level Data - Reuse of Vocabularies and Related Use Cases
Statistical Analyses of Named Entity Disambiguation Benchmarks
Statistical Analyses of Named Entity Disambiguation Benchmarks
Csongor Nyulas
Csongor Nyulas
88bb713ff705a7fe7262fda87b705b31118e76b8
Pavel Shvaiko
Pavel Shvaiko
Jeen Broekstra
Jeen Broekstra
Umair Ul Hassan
Umair Ul Hassan
NLP for Interlinking Multilingual LOD
Web Directions South
Web Directions South
Ying Ding
Ying Ding
A Role for Provenance in Social Computation
Semantic Web Challenge 2
Discovering Related Data Sources in Data-Portals
Discovering Related Data Sources in Data-Portals
University of Manchester
University of Manchester
IOS Press
IOS Press
Peter Fox
Peter Fox
Robert Hoehndorf
Robert Hoehndorf
Crowdsourced Entity Markup
Boyan Brodaric
Boyan Brodaric
Edward Curry
Edward Curry
0a02d1555c8d88a05f6a579057f7f9319e744f99
University of Milan Bicocca
University of Milan Bicocca
OLAP Manipulations on RDF Data following a Constellation Model
OLAP Manipulations on RDF Data following a Constellation Model
Federico Michele Facca
Federico Michele Facca
Adaptive Navigation through Semantic Annotations and Service Descriptions
National Technical University of Athens
National Technical University of Athens
SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing
Milan Stankovic
Milan Stankovic
Chris Biemann
Chris Biemann
Design and generation of Linked Clinical Data Cubes
Design and generation of Linked Clinical Data Cubes
Hideto Sato
Hideto Sato
Michael Granitzer
Michael Granitzer
bdd721879814228c3059502b927444eeb559cafb
Semantic Interpretation of Mobile Phone Records Exploiting Background Knowledge
Royal Institute of Technology
Royal Institute of Technology
Crowdsourced Semantics with Semantic Tagging: Don’t just tag it, LexiTag it!
John McCrae
John McCrae
Towards Linked Statistical Data Analysis
Towards Linked Statistical Data Analysis
Terunobu Kume
Terunobu Kume
Nicholas Gibbins
Nicholas Gibbins
Antoine Zimmermann
Antoine Zimmermann
Tatiana Lesnikova
Tatiana Lesnikova
Matthias Nickles
Matthias Nickles
University of Münster
University of Münster
A Search Interface for Researchers to Explore Affinities in a Linked Data Knowledge Base
A Search Interface for Researchers to Explore Affinities in a Linked Data Knowledge Base
Research information is widely available on the Web. Both as peer-reviewed research publications or as resources shared via (micro)blogging platforms or other Social Media. Usually the platforms supporting this information exchange have an API that allows access to the structured content. This opens a new way to search and explore research information. In this paper, we present an approach that visualizes interactively an aligned knowledge base of these resources. We show that visualizing resources, such as conferences, publications and proceedings, expose affnities between researchers and those resources. We characterize each affinity, between researchers and resources, by the amount of shared interests and other commonalities.
Yongbin Liu
Yongbin Liu
University of Alberta
University of Alberta
Lancaster University
Lancaster University
Davide Taibi
Davide Taibi
af81c5913a12003ea4dd36ea824f3ad467cef042
A Restful Interface for RDF Stream Processors
A Restful Interface for RDF Stream Processors
This poster proposes a minimal, backward compatible and combinable restful interface for RDF Stream Engine.
Samsung R&D
Samsung R&D
52◦ North
52◦ North
FORTH-ICS
FORTH-ICS
Real-time RDF extraction from unstructured data streams
Real-time RDF extraction from unstructured data streams
The vision behind the Web of Data is to extend the current document-oriented Web with machine-readable facts and structured data, thus creating a representation of general knowledge. However, most of the Web of Data is limited to being a large compendium of encyclopedic knowledge describing entities. A huge challenge, the timely and massive extraction of RDF facts from unstructured data, has remained open so far. The availability of such knowledge on the Web of Data would provide significant benefits to manifold applications including news retrieval, sentiment analysis and business intelligence. In this paper, we address the problem of the actuality of the Web of Data by presenting an approach that allows extracting RDF triples from unstructured data streams. We employ statistical methods in combination with deduplication, disambiguation and unsupervised as well as supervised machine learning techniques to create a knowledge base that reflects the content of the input streams. We evaluate a sample of the RDF we generate against a large corpus of news streams and show that we achieve a precision of more than 85%.
Clark & Parsia
Clark & Parsia
Haklae Kim
Haklae Kim
Hoan Nguyen Mau Quoc
Hoan Nguyen Mau Quoc
OCLC
OCLC
Industry 2
TripleRush
TripleRush
TripleRush is a parallel in-memory triple store designed to address the need for efficient graph stores that answer queries over large-scale graph data fast. To that end it leverages a novel, graph-based architecture. Specifically, TripleRush is built on our parallel and distributed graph processing framework Signal/Collect. The index structure is represented as a graph where each index vertex corresponds to a triple pattern. Partially matched queries are routed in parallel along different paths of this index structure. We show experimentally that TripleRush takes about a third of the time to answer queries compared to the fastest of three state-of-the-art triple stores, when measuring time as the geometric mean of all queries for two common benchmarks.
Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation
Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation
Research effort in ontology visualization has largely focused on developing new visualization techniques. At the same time, researchers have paid less attention to investigating the usability of common visualization techniques that many practitioners regularly use to visualize ontological data. In this paper, we focus on two popular ontology visualization techniques: indented tree and graph. We conduct a controlled usability study with an emphasis on the effectiveness, efficiency, workload and satisfaction of these visualization techniques in the context of assisting users during evaluation of ontology mappings. Findings from this study have revealed both strengths and weaknesses of each visualization technique. In particular, while the indented tree visualization is more organized and familiar to novice users, subjects found the graph visualization to be more controllable and intuitive without visual redundancy, particularly for ontologies with multiple inheritance.
DRETa: Extracting RDF from Wikitables
DRETa: Extracting RDF from Wikitables
Tables are widely used in Wikipedia articles to display relational information – they are inherently concise and information rich. However, aside from info-boxes, there are no automatic methods to exploit the integrated content of these tables. We thus present DRETa: a tool that uses DBpedia as a reference knowledge-base to extract RDF triples from generic Wikipedia tables.
Life Science
Jacco van Ossenbruggen
Jacco van Ossenbruggen
Arnab Dutta
Arnab Dutta
Patrice Seyed
Patrice Seyed
a93cde0d56e3834d06f16047565e1149ea578659
The Logic of Extensional RDFS
The Logic of Extensional RDFS
The normative version of RDF Schema (RDFS) gives non-standard (intensional) interpretations to some standard notions such as classes and properties, thus departing from standard set-based semantics. In this paper we develop a standard set-based (extensional) semantics for the RDFS vocabulary while preserving the simplicity and computational complexity of deduction of the intensional version. This result can positively impact current implementations, as reasoning in RDFS can be implemented following common set-based intuitions and be compatible with OWL extensions.
SSWS 2013 Session 1
Geo-Spatial Semantics
Adding Time to Linked Data: A Generic Memento proxy through PROV
Adding Time to Linked Data: A Generic Memento proxy through PROV
Linked Data resources change rapidly over time, making a valid consistent state difficult. As a solution, the Memento framework offers content negotiation in the datetime dimension. However, due to a lack of formally described versioning, every server needs a costly custom implementation. In this poster paper, we exploit published provenance of Linked Data resources to implement a generic Memento servics. Based on the w3c prov standard, we propose a loosely coupled architecture that offers a Memento interface to any Linked Data service publishing provenance.
Pol Mac Aonghusa
Pol Mac Aonghusa
88917e19804f860a926aef5a59812c31ae2039ae
SLUBM: An extented LUBM Benchmark for Stream Reasoning
University of Potsdam
University of Potsdam
Empirical Study of Logic-Based Modules: Cheap Is Cheerful
Empirical Study of Logic-Based Modules: Cheap Is Cheerful
For ontology reuse and integration, a number of approaches have been devised that aim at identifying modules, i.e., suitably small sets of “relevant” axioms from ontologies. Here we consider three logically sound notions of modules: MEX modules, only applicable to inexpressive ontologies; modules based on semantic locality, a sound approximation of the first; and modules based on syntactic locality, a sound approximation of the second (and thus the first), widely used since these modules can be extracted from OWL DL ontologies in time polynomial in the size of the ontology. In this paper we investigate the quality of both approximations over a large corpus of ontologies, using our own implementation of semantic locality, which is the first to our knowledge. In particular, we show with statistical significance that, in most cases, there is no difference between the two module notions based on locality; where they differ, the additional axioms can either be easily ruled out or their number is relatively small. We classify the axioms that explain the rare differences into four kinds of “culprits” and discuss which of those can be avoided by extending the definition of syntactic locality. Finally, we show that differences between MEX and locality-based modules occur for a minority of ontologies from our corpus and largely affect (approximations of ) expressive ontologies – this conclusion relies on a much larger and more diverse sample than existing comparisons between MEX and syntactic locality-based modules.
Alejandro Flores
Alejandro Flores
146e86437b6b896420ce4ba619d1eb923b9e8f88
Europeana
Europeana
Jacek Kopecky
Jacek Kopecky
Enriching Concept Search across Semantic Web Ontologies
Enriching Concept Search across Semantic Web Ontologies
Semantic Web ontologies are fast-growing knowledge sources on the Web. Searching relevant concepts from this large repository is a challenging problem. The current Semantic Web search engines provide either (1) coarse-grained search over ontologies or (2) very fine-grained search over individuals. We believe searching and ranking concepts across ontologies provides an ideal granularity for certain tasks such as ontology population and web page annotation. Towards this objective, we propose a novel approach of indexing concepts using ontology axioms in an inverted file structure and ranking them using a dynamic ranking algorithm. Our proposed method is generic and domain-independent. A preliminary evaluation indicates that our proposed method is effective, outperforming the search function of BioPortal, a large and widely-used ontology repository.
Open Door Meeting of the W3C RDF Stream Processing Community Group
Seoul National University
Seoul National University
Maribel Acosta
Maribel Acosta
Completeness Statements about RDF Data Sources and Their Use for Query Answering
Completeness Statements about RDF Data Sources and Their Use for Query Answering
With thousands of RDF data sources available on the Web covering disparate and possibly overlapping knowledge domains, the problem of providing high-level descriptions (in the form of metadata) of their content becomes crucial. In this paper we introduce a theoretical framework for describing data sources in terms of their completeness. We show how existing data sources can be described with completeness statements expressed in RDF. We then focus on the problem of the completeness of query answering over plain and RDFS data sources augmented with completeness statements. Finally, we present an extension of the completeness framework for federated data sources.
Ralf Möller
Ralf Möller
Distributed SPARQL Throughput Increase: On the effectiveness of Workload-driven RDF partitioning
Distributed SPARQL Throughput Increase: On the effectiveness of Workload-driven RDF partitioning
The Web of Data (WoD) continues to grow steadily each year. At over 31 billion triples in 2011, querying this globally distributed data space poses several scalability challenges. One critical aspect when processing distributed SPARQL queries is given by the number and type of distributed joins needed. Traditionally, query optimizers alleviate this issue by attempting to find an optimal query plan assuming a given and fixed data distribution. Discarding this fixed data partitioning assumption, offers the opportunity to create a data distribution that minimizes the number of distributed joins. Recent research focused on data- and query-driven partitioning strategies for both RDF and relational data. In this paper we propose a novel and naive workload-driven approach to data partitioning and investigate the impact of various critical factors on the number of resulting distributed joins. In a preliminary experiment we empirically compare our method to traditional partitioning strategies using a DBpedia query log of 400’000 queries and observe that it can produce up to 50% less distributed joins than an expert (manual) partitioning scheme, 45% less than partitioning based on hashing by subject and up to 83% less distributed joins than just random assignment.
Andrey Gubichev
Andrey Gubichev
9ec2c6d10bc1707dd4b16f11bdbca2a0ac1ab219
Alethia Hume
Alethia Hume
Alvaro Graves
Alvaro Graves
Guilin Qi
Guilin Qi
Albin Ahmeti
Albin Ahmeti
Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam
Fabrizio Celli
Fabrizio Celli
Ramanathan V. Guha
Ramanathan V. Guha
Controlled Query Evaluation over OWL 2 RL Ontologies
Controlled Query Evaluation over OWL 2 RL Ontologies
We study confidentiality enforcement in ontology-based information systems where ontologies are expressed in OWL 2 RL, a profile of OWL 2 that is becoming increasingly popular in Semantic Web applications. We formalise a natural adaptation of the Controlled Query Evaluation (CQE) framework to ontologies. Our goal is to provide CQE algorithms that (i) ensure confidentiality of sensitive information; (ii) are efficiently implementable by means of RDF triple store technologies; and (iii) ensure maximality of the answers returned by the system to user queries (thus restricting access to information as little as possible). We formally show that these requirements are in conflict and cannot be satisfied without imposing restrictions on ontologies. We propose a fragment of OWL 2 RL for which all three requirements can be satisfied. For the identified fragment, we design a CQE algorithm that has the same computational complexity as standard query answering and can be implemented by relying on state-of-the-art triple stores.
Semantic tools for improving software development in open source communities
Semantic tools for improving software development in open source communities
Software development communities use different communication channels such as mailing lists, forums and bug tracking systems. These channels are not integrated which makes finding information difficult and inefficient. As a result of the ALERT project we developed a system that is able to collect and annotate information from various communication channels and store it in a single knowledge base. Using the stored knowledge the system can provide users valuable functionalities such as semantic search, finding potential bug duplicates, custom notifications and issue recommendations.
IncMap: Pay as you go Matching of Relational Schemata to OWL Ontologies
IncMap: Pay as you go Matching of Relational Schemata to OWL Ontologies
Ontology Based Data Access (OBDA) enables access to relational data with a complex structure through ontologies as conceptual domain models. A key component of an OBDA system are mappings between the schematic elements in the ontology and their correspondences in the relational schema. Today, in existing OBDA systems these mappings typically need to be compiled by hand. In this paper we present IncMap, a system that supports a semiautomatic approach for matching relational schemata and ontologies. Our approach is based on a novel matching technique that represents the schematic elements of an ontology and a relational schema in a unified way. Finally, IncMap can extend user-verified mapping suggestions in a pay as you go fashion.
Pattern Based Knowledge Base Enrichment
Pattern Based Knowledge Base Enrichment
Although an increasing number of RDF knowledge bases are published, many of those consist primarily of instance data and lack sophisticated schemata. Having such schemata allows more powerful querying, consistency checking and debugging as well as improved inference. One of the reasons why schemata are still rare is the effort required to create them. In this article, we propose a semi-automatic schemata construction approach addressing this problem: First, the frequency of axiom patterns in existing knowledge bases is discovered. Afterwards, those patterns are converted to SPARQL based pattern detection algorithms, which allow to enrich knowledge base schemata. We argue that we present the first scalable knowledge base enrichment approach based on real schema usage patterns. The approach is evaluated on a large set of knowledge bases with a quantitative and qualitative result analysis.
JWS Lunch
Tu Ngoc Nguyen
Tu Ngoc Nguyen
Manfred Hauswirth
Manfred Hauswirth
ddb493a8a7c94cb9fc0c6e8d108ce0f62fee6f06
Editing R2RML Mappings Made Easy.
Editing R2RML Mappings Made Easy.
The new W3C standard R2RML\footnote{See: http://www.w3.org/TR/r2rml/} defines a language for expressing mappings from relational databases to RDF, allowing applications built on top of the W3C Semantic Technology stack to seamlessly integrate relational data. A major obstacle in using R2RML, though, is the creation and maintenance of mappings. In this demo, we present a novel R2RML mapping editor, which provides a user interface to create and edit mappings interactively. Hiding the R2RML vocabulary intricacies from the user, the editor enables even non-experts to create R2RML mappings in a guided way, offers immediate feedback by means of integrated preview functionality, and covers all the major language constructs defined in the R2RML standard.
Federated Entity Search using On-The-Fly Consolidation
Society, Privacy and the Semantic Web - Policy and Technology
A Confidentiality Model for Ontologies
A Confidentiality Model for Ontologies
We illustrate several novel attacks to the confidentiality of knowledge bases (KB). Then we introduce a new confidentiality model, sensitive enough to detect those attacks, and a method for constructing secure KB views. We identify safe approximations of the background knowledge exploited in the attacks; they can be used to reduce the complexity of constructing secure KB views.
Break
Introduction Talk: Research Questions and Scientific Hypotheses
2nd International Workshop on Ordering and Reasoning
Veli Bicer
Veli Bicer
7606e0abc2772f43ae5c0d0264160bfe8a22acc3
TRM – Learning Dependencies between Text and Structure with Topical Relational Models
TRM – Learning Dependencies between Text and Structure with Topical Relational Models
Text-rich structured data become more and more ubiquitous on the Web and on the enterprise databases by encoding heterogeneous structural information between entities such as people, locations, or organizations and the associated textual information. For analyzing this type of data, existing topic modeling approaches, which are highly tailored toward document collections, require manually-defined regularization terms to exploit and to bias the topic learning towards structure information. We propose an approach, called Topical Relational Model, as a principled approach for automatically learning topics from both textual and structure information. Using a topic model, we can show that our approach is effective in exploiting heterogeneous structure information, outperforming a state-of-the-art approach that requires manually-tuned regularization.
Morning Tea
Miel Vander Sande
Miel Vander Sande
ab7f79520d96c603dc26cecea0533fc098d8d9af
Freudenberg IT
Freudenberg IT
University of Naples Federico II
University of Naples Federico II
Takahide Matsutsuka
Takahide Matsutsuka
Oscar Corcho
Oscar Corcho
1st International Workshop on Semantic Music and Media
Simon Razniewski
Simon Razniewski
279b9d72c9d959d4f93219e45a9d41fc980ad9b9
Lunch
IBM Research
IBM Research
Ricardo Falbo
Ricardo Falbo
Yefei Peng
Yefei Peng
Posters & Demos Session
Jonathan Mortensen
Jonathan Mortensen
Eviction Strategies for Semantic Flow Processing
Timo Weber
Timo Weber
Rafik Saad
Rafik Saad
Carsten Keßler
Carsten Keßler
German Research Centre for Artificial Intelligence
German Research Centre for Artificial Intelligence
Joao Ricardo Nickenig Vissoci
Joao Ricardo Nickenig Vissoci
6a04f2f4996d6074601f5597edf32d7286a73e49
Markus Strohmaier
Markus Strohmaier
Getting Lucky in Ontology Search: A Data-Driven Evaluation Framework for Ontology Ranking
Afternoon Tea
Technische Universität Darmstadt
Technische Universität Darmstadt
Guus Schreiber
Guus Schreiber
Jane Taggart
Jane Taggart
f978fc491289b03a4759f2a7db6e753167e2ab04
Markus Krötzsch
Markus Krötzsch
Andreas Schwarte
Andreas Schwarte
0847584827dd629eacd2ba195d7e9bfea4113c9c
Entity recommendations in Web Search
Minute Madness
Dougald Hine
Dougald Hine
Aisha Naseer
Aisha Naseer
Jim Burton
Jim Burton
Eero Hyvönen
Eero Hyvönen
John Domingue
John Domingue
Tim Finin
Tim Finin
Yrjana Rankka
Yrjana Rankka
40fe2ecb35517577d5de77f8c4c846c283376b8e
Kevin Page
Kevin Page
Gerhard Weikum
Gerhard Weikum
Towards Easy Matching Between Statistical Linked Data: Dimension Patterns
Ernesto WilliamDe Luca
Ernesto WilliamDe Luca
Giancarlo Guizzardi
Giancarlo Guizzardi
LISC 2013 Session 1
Sambhawa Priya
Sambhawa Priya
974b04e6905f6a70f94024e5973cb6722ea9ef60
SpazioDati
SpazioDati
David Toman
David Toman
3d7f41f9bf76c4915e93d816b0e385eb76c80910
Amanda Castray
Amanda Castray
SWJ Dinner
Opportunities created for agricultural and environmental informatics through whole-of-economy federated sensing
Design and generation of Linked Clinical Data Cubes
Ali Khalili
Ali Khalili
Australian Bureau of Statistics
Australian Bureau of Statistics
Martin Ebner
Martin Ebner
8ae731106b9f503898d71d7980bd10f58071f7e7
PRIVON 2013 Session 2
Data Integration and Inter-linking
Evgeniy Birialtsev
Evgeniy Birialtsev
5fc120d15c22a58c4fd4d7449bb06a327359765a
Matthias Krause
Matthias Krause
Towards the Discovery of Person-Level Data - Reuse of Vocabularies and Related Use Cases
Griffith University
Griffith University
PRIVON 2013 Session 1
Bijan Parsia
Bijan Parsia
c9ef3edda6fd12cc1e9113217a75e5074e2ee80e
Anna Fensel
Anna Fensel
Aba-Sah Dadzie
Aba-Sah Dadzie
Lee Harland
Lee Harland
2d7b8a8e4b9b198f6a295a027f714536c69435ef
IICM - Institute for Information Systems and Computer Media
IICM - Institute for Information Systems and Computer Media
OpenLink Software
OpenLink Software
XKOS: Extending SKOS for Describing Statistical Classifications
PRIVON 2013 Session 4 - Parallel Open Space Discussions Report back from Open Space and Follow Up actions
Maarten Wijnants
Maarten Wijnants
4c48d52a475f559b7d8c502c135a60d7e49a4316
Jörg Unbehauen
Jörg Unbehauen
University of Illinois at Urbana–Champaign
University of Illinois at Urbana–Champaign
LISC 2013 Session 3
American University of Beirut
American University of Beirut
Morning Tea
SML2OD 2013 Session 2
Claudia Wagner
Claudia Wagner
Mischa Tuffield
Mischa Tuffield
PRIVON 2013 Session 3 - Parallel Open Space Discussions
Iina Hellsten
Iina Hellsten
Dimitrios Georgakopoulos
Dimitrios Georgakopoulos
23ce57b2a13bbe7eb0bef3bc9082d377dcb1fb18
Application Building on the Web
Dianna Madden
Dianna Madden
Christopher Brink
Christopher Brink
Lunch
SML2OD 2013 Session 1
Payam Barnaghi
Payam Barnaghi
Linked Data for Web Scale Information Extraction Session 2
Louiqa Raschid
Louiqa Raschid
A knowledge-based approach to computational analysis of melody in Indian art music
A knowledge-based approach to computational analysis of melody in Indian art music
LISC 2013 Session 2
Jose Sanchez
Jose Sanchez
512641f84135a3e4ee42e71cb4952d45058ea496
IIT Bombay
IIT Bombay
Agata Filipowska
Agata Filipowska
Registration
Shuangjie Li
Shuangjie Li
Semantic Metadata for Music Production Projects
Semantic Metadata for Music Production Projects
Pieter De Leenheer
Pieter De Leenheer
OM-2013 Discussion and wrap-up
Ehab Hassan
Ehab Hassan
Research Track
Announcements
Yonsei University
Yonsei University
Jun Zhao
Jun Zhao
Fedelucio Narducci
Fedelucio Narducci
22e45a1e8b5cea2f9c18b802460b09eb66c09c25
Terry Roach
Terry Roach
9th International Workshop on Scalable Semantic Web Knowledge Base Systems
Learning Classifiers from Semantic Sensor Data with Application to Soil Drainage Classification
Elastic and scalable processing of Linked Stream Data in the Cloud
Christina Unger
Christina Unger
Workshop Introduction
Harris Lin
Harris Lin
A Rule-Based Relation Extraction System using DBpedia and Syntactic Parsing
A Rule-Based Relation Extraction System using DBpedia and Syntactic Parsing
Ahmet Soylu
Ahmet Soylu
b281e352fdfa9c82f9c80899b36a0b9e9cf97eaa
Social listening of City Scale Events using the Streaming Linked Data Framework
Anupam Joshi
Anupam Joshi
de4984eb69b9610f133321ac8b1fc38de56661e3
John Breslin
John Breslin
Learning about Activities from Spatio Temporal Data
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
Rudi Studer
Rudi Studer
Roger Menday
Roger Menday
Keynote
Gunnar Aastrand Grimnes
Gunnar Aastrand Grimnes
Mikalai Tsytsarau
Mikalai Tsytsarau
0f6f5fcbc1ef9874795eb52700cb8d0e21ecbde0
LISC 2013 Session 4 (Co-writing)
Representing Supply Chain Events on the Web of Data
Lyndon Nixon
Lyndon Nixon
Semantic Web Enabled Smart Farming
On Correctness in RDF stream processor benchmarking
SSWS 2013 Session 3
Stuart Owen
Stuart Owen
61f287b86d0ee15dafdf85b41a3d6cb52412d820
Choosing Between Graph Databases and RDF Engines for Consuming and Mining Linked Data
Guillermo Palma
Guillermo Palma
ec8c21a30b57df2d5a8b55e8e3a0723ec3446bd0
Arash Shaban-Nejad
Arash Shaban-Nejad
a2b7f345891c743b0f88d69accc28ea1e590e48b
Miguel Esteban Gutiérrez
Miguel Esteban Gutiérrez
University of Graz
University of Graz
Laurens De Vocht
Laurens De Vocht
dd9795b45b273afe8ee3edfb66a6e4e8f6f677f9
Extractivism: Extracting activist events from news articles using existing NLP tools and services
Semantic Message Passing for Generating Linked Data from Tables
SRI International
SRI International
Real-time Urban Monitoring in Dublin using Semantic and Stream Technologies
Austrian Environmental Data Consumption – A Mashup-based Approach
Event Object Boundaries in RDF Streams: A Position Paper
SSWS 2013 Session 2
Sara Tonelli
Sara Tonelli
9c5d5a9c69c3005788845b736d4460cb53a048e5
Yavor Nenov
Yavor Nenov
A case study on automated risk assessment of ships using newspaper-based event extraction
Martin Hepp
Martin Hepp
Early warning system for coffee rust disease based on error correcting output codes: a proposal
Michael Smethurst
Michael Smethurst
85be2aefd28bddb1ff44518689f7f20ef372501b
Fiona McNeill
Fiona McNeill
University of Koblenz and Landau
University of Koblenz and Landau
Georg Lausen
Georg Lausen
9b94eccc1de49ceee1f8fe147ffa5e994a5080af
Real-time RDF extraction from unstructured data streams
Linked Open Robot Data
Aalto University
Aalto University
University of California, Santa Barbara
University of California, Santa Barbara
Giovanni Semeraro
Giovanni Semeraro
b3f6d3de29e2af119e49a6d82ee229b5dde61452
AgroKnowledgeBase (AKB) for plant diseases: Poppy plant use case
Christina Feilmayr
Christina Feilmayr
Sam Coppens
Sam Coppens
d13779a648af2d2d2da34f2d758084f5624debd0
Iliya Enchev
Iliya Enchev
76514d5af4d44bc96ab44c88e09a9b23474b9f93
Antonis Loizou
Antonis Loizou
0e56fcf7988a7c4b8cebd03edf90ea8bd630346c
SMAM 2013 Session 1
University of Technology, Sydney
University of Technology, Sydney
Freelance Technologist
Freelance Technologist
Pierpaolo Tommasi
Pierpaolo Tommasi
7fc9c74bf9b38cba0a03f49609524524e9a449e1
Freddy Lecue
Freddy Lecue
67563701b5a8a32071b3104f293650643518ee67
Yuzhong Qu
Yuzhong Qu
57682429d3d2a18d6a9c2c2b0559a2105ca034a1
The role of vocabularies for estimating carbon footprint for food recipies using Linked Open Data
Pavel Klinov
Pavel Klinov
3a137941f3fcc707bf5e8d34cadae4addf400736
ca5eb3e91da52502e360f9a7a398548420bac5f1
Heiko Mueller
Heiko Mueller
SMAM 2013 Session 2
Integrating Open and Closed Information Extraction: Challenges and First Steps
Integrating Open and Closed Information Extraction: Challenges and First Steps
Yahoo! Labs
Yahoo! Labs
Television meets the Web: a Multimedia Hypervideo Experience
Universidad Politecnica de Madrid(UPM)
Universidad Politecnica de Madrid(UPM)
DynamiTE: Parallel Materialization of Dynamic RDF Data
Hans Constandt
Hans Constandt
Sean Bechhofer
Sean Bechhofer
Lorenz Fischer
Lorenz Fischer
0471e838fcc1f34c6ab480ae5bf0f5669ea2fec3
Frame Semantics Annotation Made Easy with DBpedia
Integrating Open and Closed Information Extraction: Challenges and First Steps
TripleRush: A Fast and Scalable Triple Store
Uroš Milošević
Uroš Milošević
Thomas Ploeger
Thomas Ploeger
The effects of Licensing on Open Data: Computing a measure of health for our Scholarly Record
Boris Motik
Boris Motik
d1822505990c7a62874033c9a382d43f94785308
Tuan Dat Trinh
Tuan Dat Trinh
Melliyal Annamalai
Melliyal Annamalai
Completeness Statements about RDF Data Sources and Their Use for Query Answering
Developing Crowdsourced Ontology Engineering Tasks: An iterative process
Extending the Coverage of DBpedia Properties using Distant Supervision over Wikipedia
Rule-based Reasoning on Massively Parallel Hardware
Lalana Kagal
Lalana Kagal
Ontology-based top-k query answering over massive, heterogeneous, and dynamic data
Qatar Computing Research Institute
Qatar Computing Research Institute
Valentina Presutti
Presutti
Valentina Presutti
Valentina Presutti
Valentina
7cdf93aba3cd434a666422057efd1e7df4bf3bac
Incremental Reasoning in OWL EL without Bookkeeping
Part III. Demos, Tools & Research directions
DistEL: A Distributed EL+ Ontology Classifier
Mingquan Zhou
Mingquan Zhou
2dfd54473d5725375ae59dcba85db4376021c507
Legibility, Privacy and Creativity: Linked Data in a Surveillance Society
CEDAR: a Fast Taxonomic Reasoner Based on Lattice Operations
CEDAR: a Fast Taxonomic Reasoner Based on Lattice Operations
Taxonomy classification and query answering are the core reasoning services provided by most of the Semantic Web (SW) reasoners. However, the algorithms used by those reasoners are based on Tableau method or Rules. These well-known methods in the literature have already shown their limitations for large-scale reasoning.In this demonstration, we shall present the CEDAR system for classifying and reasoning on very large taxonomies using a technique based on lattice operations. This technique makes the CEDAR reasoner perform on a par with the best systems for concept classification and several orders-of-magnitude more efficiently in terms of response time for query-answering. The experiments were carried out using very large taxonomies (Wikipedia: 111599 sorts, MESH: 286381 sorts, NCBI: 903617 sorts and Biomodels: 182651 sorts). The results achieved by CEDAR were compared to those obtained by well-known Semantic Web reasoners, namely FaCT++, Pellet, HermiT, TrOWL, SnoRocket and RacerPro.
Stuart Brown
Stuart Brown
584941e620ba67f061ae9612718ff52da8da1a5f
Ontology Evolution for End-User Communities
Semantic Web Science Association
Semantic Web Science Association
Chen Zheng
Chen Zheng
556a7b8b1f30cb15068ce4c800b99557831cb662
ISTI-CNR
ISTI-CNR
Dunja Mladenic
Dunja Mladenic
Part II. Big Data Algorithms (cont.)
Fabien Gandon
Fabien Gandon
583b2ab35d1cef69e21b25a7f36ec5a36e11d31d
Michael Pizzo
Michael Pizzo
Samir Amir
Samir Amir
351550524d630236d70ed31f82c73f90e0395d50
Rik Van de Walle
Rik Van de Walle
209af6a5da064a4a0f0cb89a336bfeb0ebcc196d
A case for transparency
Demonstrating The Entity Registry System: Implementing 5-Star Linked Data Without the Web
Demonstrating The Entity Registry System: Implementing 5-Star Linked Data Without the Web
Linked Data applications often assume that connectivity to data repositories and entity resolution services are always available. This may not be a valid assumption in many cases. Indeed, there are about 4.5 billion people in the world who have no or limited Web access. Many data-driven applications may have a critical impact on the life of those people, but are inaccessible to those populations due to the architecture of today's data registries. In this demonstration, we show a new open-source system that can be used as a general-purpose entity registry suitable for deployment in poorly-connected or ad-hoc environments.
Andreas Wagner
Andreas Wagner
One License to Compose Them All: a deontic logic approach to data licensing on the Web of Data
Chris Welty
Chris Welty
Exploiting Information Extraction and the Semantic Web at Yahoo Search
Michel Gagnon
Michel Gagnon
LIRMM
LIRMM
Salman Haq
Salman Haq
Mounira Chkiwa
Mounira Chkiwa
Luc Moreau
Luc Moreau
Maxime Lavigne
Maxime Lavigne
666083d5a5416cd3b87495a8c171940c2245e8a9
Takahira Yamaguchi
Takahira Yamaguchi
Isao Kojima
Isao Kojima
233d4325ae7e1c3833a869e076d87ab6dbd528fa
Marc Schaaf
Marc Schaaf
University of Oslo
University of Oslo
Sandro Hawke
Sandro Hawke
NoHR: Querying EL with Non-monotonic rules
NoHR: Querying EL with Non-monotonic rules
We present NoHR, a Protege plug-in that allows the user to take an EL ontology, add a set of non-monotonic (logic programming) rules - suitable e.g. to express defaults and exceptions - and query the combined knowledge base. Provided the given ontology alone is consistent, the system is capable of dealing with potential inconsistencies between the ontology and the rules, and, after an initial brief pre-processing period utilizing OWL 2 EL reasoner ELK, returns answers to queries at an interactive response time by means of XSB Prolog.
Industry 3
Rachele Sprugnoli
Rachele Sprugnoli
7603c4d8c16526bb57e0f0bc048b7322d7eed711
A Confidentiality Model for Ontologies
Microtask tutorial session 4
The Object with States Ontology Design Pattern
The Object with States Ontology Design Pattern
Thomas Krennwallner
Thomas Krennwallner
Extending DBpedia with Wikipedia List Pages
Timo Willemsen
Timo Willemsen
Evgenij Thorstensen
Evgenij Thorstensen
8aecba9cd04ad3f4b089264ec76feb9fe8aac0f5
Matthias Knorr
Matthias Knorr
c914e6f10c9b076414ed123a8545e233074e8b37
Evelyne Viegas
Evelyne Viegas
Semantic Web vs. Privacy: Menace or opportunity?
Search
WOP 2013 Session 1
On the Semantics of R2RML and its Relationship with the Direct Mapping
On the Semantics of R2RML and its Relationship with the Direct Mapping
The W3C Relational Database to RDF (RDB2RDF) standards are positioned to bridge the gap between Relational Databases and the Semantic Web. The standards consist of two interrelated and complementary specifications: “Direct Mapping of Relational Data to RDF” and “R2RML: RDB to RDF Mapping Language”. In this paper we present initial results on the formal study of the R2RML mapping language by defining its semantics using Datalog. We prove that there are a total of 57 distinct Datalog rules which can be used to generate RDF triples from a relational table. Additionally, we provide insights on the relationship between R2RML and Direct Mapping.
Yannis Kalfoglou
Yannis Kalfoglou
3rd International Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web
Dimitris Kontokostas
Dimitris Kontokostas
DBpediaNYD A Silver Standard Benchmark Dataset for Semantic Relatedness in Dbpedia
Pierre-Yves Vanderbussche
Pierre-Yves Vanderbussche
An FCA Framework for Knowledge Discovery in SPARQL Query Answers
An FCA Framework for Knowledge Discovery in SPARQL Query Answers
Formal concept analysis (FCA) is used for knowledge discovery within data. In FCA, concept lattices are very good tools for classification and organization of data, hence, they enable the user to visualize the answers of its SPARQL query as concept lattices instead of the usual answer formats such as: RDF/XML, JSON, CSV, and HTML. Consequently, in this work, we apply FCA to reveal hidden relations within SPARQL query answers by means of concept lattices.
WOP 2013 Session 2 Poster
Natural Language Processing
Informatica Trentina
Informatica Trentina
Kemafor Anyanwu
Kemafor Anyanwu
Joachim Wackerow
Joachim Wackerow
Sabrina Kirrane
Sabrina Kirrane
320d9f4a9a8e46a3db97763af6cb481e3c6981db
Mikko Rinne
Mikko Rinne
Deborah McGuinness
Deborah McGuinness
292f7f25a21bd6c41c784397092317016dfc987d
A Study on the Correspondence between FCA and $\mathcal{ELI}$ Ontologies
A Study on the Correspondence between FCA and $\mathcal{ELI}$ Ontologies
The description logic $\mathcal{EL}$ has been used to support ontology design in various domains, and especially in biology and medecine. $\mathcal{EL}$ is known for its efficient reasoning and query answering capabilities. By contrast, ontology design and query answering can be supported and guided within an FCA framework. Accordingly, in this paper, we propose a formal transformation of $\mathcal{ELI}$ (an extension of $\mathcal{EL}$ with \textit{inverse roles}) ontologies into an FCA framework, i.e. $K_\mathrm{\mathcal{ELI}}$, and we provide a formal characterization of this transformation. Then we show that SPARQL query answering over $\mathcal{ELI}$ ontologies can be reduced to lattice query answering over $K_\mathrm{\mathcal{ELI}}$ concept lattices. This simplifies the query answering task and shows that some basic semantic web tasks can be improved when considered from an FCA perspective.
A lemon lexicon for DBpedia
Emir Muñoz
Emir Muñoz
da29212ff6bcf3de75e664694436e6ba808db98b
Afternoon Tea
Phil Archer
Phil Archer
Using Ontologies to Identify Patients with Diabetes in Electronic Health Records
Using Ontologies to Identify Patients with Diabetes in Electronic Health Records
This paper describes a work in progress that explores the applicability of ontology for providing solutions in medical domain. We investigate whether it is feasible to use ontologies and ontology-based data access to automate one of common clinical tasks that are constantly faced by general practitioners but labor intensive and error prone in term of relevant information retrieved from electronic health records. The focus of our study is on improving diabetes patient selection for clinical trials or medical research. The biggest impediment to automating such clinical tasks is the essential requirement of bridging the semantic gaps between existing patient data from electronic health records, such as reasons for visit, chronic conditions and diagnoses from practice notes, pathology tests and prescriptions stored in general practice information systems, and the ways which researchers or general practitioners interpret those records. Our current comprehension is that automation of identifying diabetes patients for clinical or research purposes can be specified systematically as a solution supported by semantic retrieval. We detail the challenges to build a realistic case study, which consists of solving issues related to conceptualization of data and domain context, integration of different datasets, ontology creation based on SNOMED CT-AU® standard, mapping between existing data and ontology, and dilemma of data fitness for research use. Our prototype is based on data which scale to thirteen years of approximate 100,000 anonymous patient records from four general practices in south western Sydney.
Paolo Bottoni
Paolo Bottoni
26740a051e22c7e574effc8ab2e983b1b6372efd
Siemens
Siemens
Microtask tutorial session 1
Computer Research Institute of Montreal
Computer Research Institute of Montreal
J. Stephen Downie
J. Stephen Downie
Monitoring SPARQL Endpoint Status
Monitoring SPARQL Endpoint Status
We demo an online system that tracks the availability of over four-hundred public SPARQL endpoints and makes up-to-date results available to the public. Our demo currently focuses on how often an endpoint is online/offline, but we plan to extend the system to collect metrics about available meta-data descriptions, SPARQL features supported, and performance for generic queries.
Town Hall
Smitashree Choudhury
Smitashree Choudhury
Towards Semantic Annotations of Web Tables
Towards Semantic Annotations of Web Tables
Web tables comprise a rich source of factual information.However, without semantic annotation of the tables’ content the infor-mation is not usable for automatic integration and search. We propose amethodology to annotate table headers with semantic type informationbased on the content of column’s cells. In our experiments on 50 tableswe achieved an F1 value of 0.55, where the accuracy greatly varies de-pending on the used ontology. Regarding computational complexity wefound out that 94% of the maximal F1 score on average 20 cells (37%)need to be considered. Results suggest that the choice of the ontologyplays a more crucial role for type inference than the number of cells used.
SSN 2013 Session 1
Microtask tutorial session 3
Oracle
Oracle
Ontotext
Ontotext
GetThere: A Rural Passenger Information System Utilising Linked Data & Citizen Sensing
GetThere: A Rural Passenger Information System Utilising Linked Data & Citizen Sensing
This demo paper describes a real-time passenger information system based on citizen sensing and linked data.
Matthew Horridge
Matthew Horridge
724478377604eb17b9def8e3b6241fc620c71c2b
Abstracting Transport to an Ontology Design Pattern for the Geosciences
Abstracting Transport to an Ontology Design Pattern for the Geosciences
Mentoring Lunch
George Garbis
George Garbis
3d5c1f8e68b6329ae8f6f6b76102c0b33ad72ab5
Jack Sun
Jack Sun
0ec7e08a5afc612b46a15d1edee9710bed43fa69
Amin Anjomshoaa
Amin Anjomshoaa
Microtask tutorial session 2
Michiel Hildebrand
Michiel Hildebrand
Workshop Introduction
University of Bremen
University of Bremen
Break
Thomas Bosch
Thomas Bosch
Workshop Summaries
Create-Net
Create-Net
Marko Grobelnik
Marko Grobelnik
Ganesh Ramakrishnan
Ganesh Ramakrishnan
b36f5c490b830f5fd6580cebb8a587ead9acb559
Amedeo Napoli
Amedeo Napoli
e41a677b5c392b0fb481e1f8fa1077c01f62785a
Électricité de France
Électricité de France
Dai Quoc Nguyen
Dai Quoc Nguyen
3d5b3abd49a28d48abd56b854e5059fc49435a24
Yingjie Hu
Yingjie Hu
83226129d02f5b7014c2e99a047a072338b90eb2
DeRiVE 2013 Session 2
Teodor Macicas
Teodor Macicas
3419c4050a3d506d58d9a3215dfa65235261227f
Royal Society of Chemistry
Royal Society of Chemistry
Amazon’s Mechanical Turk hands-on
DeRiVE 2013 Session 1
Ruben Verborgh
Ruben Verborgh
fb22bc1100f1f5b282380024f58bf4e906fd3e69
Thomas Lukasiewicz
Thomas Lukasiewicz
Jonathan Queipo
Jonathan Queipo
e76c73a9393697a4b7d340cfe8e21c8eeccee113
Concordia University
Concordia University
Nico Adams
Nico Adams
Daniel Kinzler
Daniel Kinzler
Wrap-up
Ondrej Svab-Zamazal
Ondrej Svab-Zamazal
Oak Ridge National Laboratory
Oak Ridge National Laboratory
Dinner Cruise
University of Waikato
University of Waikato
Werner Nutt
Werner Nutt
048d577a29b6c35abf950e3201dff43fecec6a27
Gem Stapleton
Gem Stapleton
Sven Hertling
Sven Hertling
cdb81c7500bf7e5617991e6455939381efcb737c
Building Exceutable Biological Pathway Models Automatically from BioPAX
SSN 2013 Session 2
Petya Osenova
Petya Osenova
Ilaria Tiddi
Ilaria Tiddi
9e46519c300f7b6321d6d2ab61bdfdb5624fa296
Web Directions
Web Directions
Bryn Williams-Jones
Bryn Williams-Jones
Riedl Reinhard
Riedl Reinhard
Alasdair J. G. Gray
Alasdair J. G. Gray
0aadcd3e209afe65c0da689b6bc93c100ac33641
Andrea Perego
Andrea Perego
Royal Military College of Canada
Royal Military College of Canada
Michael D. Huhns
Michael D. Huhns
Stefan Dietze
Stefan Dietze
ee6dc5ffc8da2b150fab3da1bcf3d788011c3312
Results may vary: reproducibility, open science and all that jazz
Maria Esther Vidal
Maria Esther Vidal
6c9651932804d271e53f279c99d7cd1d1d429c0a
Conclusions and discussion
Announcements
Ziqi Zhang
Ziqi Zhang
c43c40fe06b847e5af5f83dbec349edabc6c1562
The Event Processing ODP
The Event Processing ODP
Filip De Turck
Filip De Turck
a7caf54a202dd5d2d7ba5a707601e3a5b06541fc
Erik Mannens
Erik Mannens
0fb8b8ec11b797cb181f04f8c7534a39dd42812c
Daniel Miranker
Daniel Miranker
0fea94336fe97522ad08d3100f2555d8b1acab05
Ora Lassila
Ora Lassila
Dezhao Song
Dezhao Song
4c3085b2c9a9fa05ddd0b0148fba4994b101ad7a
tablet-based visualisation of transport data in Madrid using SPARQL-Stream
Fabian M. Suchanek
Fabian M. Suchanek
Morning Tea
Lise Getoor
Lise Getoor
a99eb4a4efc181fdeb7576c2202d0cfe4c0154fc
Valeria Pestana
Valeria Pestana
65033795873d0ea0732e3c67442976a0067b8ee3
Felix Sasaki
Felix Sasaki
Quyen Ngyuen
Quyen Ngyuen
Jie Bao
Jie Bao
Yeungnam University
Yeungnam University
Diagrammatic Ontology Patterns
Diagrammatic Ontology Patterns
Simone Ponzetto
Simone Ponzetto
Anis Jedidi
Anis Jedidi
Liliana Cabral
Liliana Cabral
Akiyoshi Matono
Akiyoshi Matono
d521b1bb0a1bf1c31532a451c92019f2dfe09bd2
Registration
License Linked Data Resources Pattern
License Linked Data Resources Pattern
Linked Data for Information Extraction: Opportunity or Babel?
Francisco M. Couto
Francisco M. Couto
6e0ac3ec27c6a3528cf198780b90a237d8d273b8
Emanuele Della Valle
Emanuele Della Valle
1ee386235c89959195075bc4944d5c68f8265f96
Tutorial Track
Adam Shepherd
Adam Shepherd
The Mobile Semantic Web Session 2
Shenghui Wang
Shenghui Wang
Harald Sack
Harald Sack
Break
From RESTful to SPARQL: A Case Study on Generating Semantic Sensor Data
Margaret-Anne Storey
Margaret-Anne Storey
9bf1dba1dec3467c029a1decb95ddda8a88d6103
Dresden University of Technology
Dresden University of Technology
Chin-Wan Chung
Chin-Wan Chung
9a2b850f734d7438c4c6ac373ac4feb08a22c0c2
Robin Keskisärkkä
Robin Keskisärkkä
OntoForce
OntoForce
Afternoon Tea
Alireza Rahimi
Alireza Rahimi
b74d4194174f9149f3dcae1e1904f485ab942dc5
Paul Groth
Paul Groth
9fef9efae9dd7807a8637669cca7452edd5675fb
Lianli Gao
Lianli Gao
Valery Tkachenko
Valery Tkachenko
380d4e41a53ea70a4079dc972ab5c6e6f33ab80c
Pablo Mendes
Pablo Mendes
f897e0cb6fdf0f9dde1ac5629ac17caebd3fd4fb
Know-Center
Know-Center
Citizen Sensing within a Real Time Passenger Information System
Lunch
Andrea Giovanni Nuzzolese
71a761b4b91daced90923b5fc2d37f7afeb2c501
Andrea Giovanni
Andrea Giovanni Nuzzolese
Nuzzolese
Andrea Giovanni Nuzzolese
Florida Institute for Human and Machine Cognition
Florida Institute for Human and Machine Cognition
Vinay Chaudhri
Vinay Chaudhri
Stefan Decker
Stefan Decker
1bc1f862b688a45b7e0c8d4a8467c23177c53fad
ISI/USC
ISI/USC
The Mobile Semantic Web Session 1
An Ontology Framework for Water Quality Management
ISWC2014 Lunch
Oana Inel
Oana Inel
University of Bologna
University of Bologna
Hannes Mühleisen
Hannes Mühleisen
3a5488a61158ce2a992a3fc5f702624490a31a7a
Nokia
Nokia
Nenad Stojanovic
Nenad Stojanovic
Kyong-Ho Lee
Kyong-Ho Lee
1fb0bc159530c38de666dc8b68f88e124e1f2a30
Ivan Mikhailov
Ivan Mikhailov
0566edd9860dfea94c16227fa751dd8c4c1fe129
Mike Jewell
Mike Jewell
Faiez Gargouri
Faiez Gargouri
Streams
Milan Dojchinovski
Milan Dojchinovski
Paulo Costa
Paulo Costa
WaSABi session 2
German Research Centre for Artificial Intelligence (DFKI)
German Research Centre for Artificial Intelligence (DFKI)
Jesper Hoeksema
Jesper Hoeksema
2e0aafe7b5307febd159ef52ca589f9defb9d48f
University of Sheffield
University of Sheffield
Giovanni Tummarello
Giovanni Tummarello
Haixun Wang
Haixun Wang
WaSABi session 1
Myriam Lamolle
Myriam Lamolle
63d6ed50ba08db26b09426a27ea93a18d1d78fc7
Yafang Wang
Yafang Wang
Craig Knoblock
Craig Knoblock
2c2715555efac793759255fe12d117541cf52a37
Bureau of Meteorology
Bureau of Meteorology
Klaus Lyko
Klaus Lyko
ISTC-CNR
ISTC-CNR
CNRS
CNRS
Antoine Isaac
Antoine Isaac
Birte Glimm
Birte Glimm
d9e3004543dab6b7586ec0c3846985b999320232
Philipp Wille
Philipp Wille
1fe66d51bb96cab8653dc1687e65f7f97407d7ab
Bernardo Pereira Nunes
Bernardo Pereira Nunes
1f87692d4f8246501797fdb8ddb5213e7d91a81e
Frank Wolter
Frank Wolter
15bacc782854191d65c92bac1366abfbc94ab335
Kai Eckert
Kai Eckert
879a31b9ba30147a3c6b355738137f2859f00ba2
Shonali Krishnaswamy
Shonali Krishnaswamy
Narges Shahmandi Hoonejani
Narges Shahmandi Hoonejani
Vienna University of Technology
Vienna University of Technology
Christian Bizer
Christian Bizer
d293ced5ef76989393dc5a8380fb9b2c89c1f083
Fujitsu
Fujitsu
University of Lausanne
University of Lausanne
Enriching Ontologies through Data
Hugo Leroux
Hugo Leroux
GIS-based Ontology on Organic Agriculture (On-going research)
GIS-based Ontology on Organic Agriculture (On-going research)
Jose Pinero
Jose Pinero
ab23d8c2ed65b52fb4077c9b214c951619682436
The Logic of Extensional RDFS
IBM Thomas J. Watson Research Center
IBM Thomas J. Watson Research Center
Umberto Straccia
Umberto Straccia
Alistair Hamilton
Alistair Hamilton
Yuefeng Li
Yuefeng Li
Guido Governatori
Guido Governatori
cef52cab17229cced5fddb67265f87b1a3b539be
Content and Behaviour Based Metrics for Crowd Truth
Approximate Reasoning and Approximate Stream Reasoning for OWL2-DL
Chan Le Van
Chan Le Van
Dat Quoc Nguyen
Dat Quoc Nguyen
2fd5e3d773e88a8795685712a886dc08f0a54944
Information Reputation
University of South Carolina
University of South Carolina
Australian Proteome Analysis Facility
Australian Proteome Analysis Facility
University of Auckland
University of Auckland
Songmao Zhang
Songmao Zhang
Zoltán Miklós
Zoltán Miklós
Hands-on session
Indented Tree or Graph? A Usability Study of Ontology Visualization Techniques in the Context of Class Mapping Evaluation
Silviu Homoceanu
Silviu Homoceanu
bc22990c2b6af7a595cdc46be6671c1723fbcecf
Count Aggregation in Semantic Queries
Context Aware Sensor Configuration Model for Internet of Things
Context Aware Sensor Configuration Model for Internet of Things
We propose a Context Aware Sensor Configuration Model (CASCoM) to address the challenge of automated context-aware configuration of filtering, fusion, and reasoning mechanisms in IoT middleware according to the problems at hand. We incorporate semantic technologies in solving the above challenges.
Sebastian Walter
Sebastian Walter
4th Workshop on Ontology Patterns
Mengling Xu
Mengling Xu
46db4db2ecee372bb32e00a99bfb02838d0bf7ca
Ekawit Nantajeewarawat
Ekawit Nantajeewarawat
Fluid Operations
Fluid Operations
NTT DoCoMo
NTT DoCoMo
Monika Lanzenberger
Monika Lanzenberger
Best-effort Linked Data Query Processing with time constraints using ADERIS-Hybrid
Best-effort Linked Data Query Processing with time constraints using ADERIS-Hybrid
Answering SPARQL queries over the Web of Linked Data is a challenging problem. Approaches based on distributed query processing provide up-to-date results but can suffer from delayed response times, indexing-based approaches provide fast response times but results can be out-of-date and the costs of indexing the growing Web of Linked Data are potentially huge. Hybrid approaches try to offer the best of both. In this demo paper we describe a system for answering SPARQL queries within fixed time constraints by accessing SPARQL endpoints and the Web of Linked Data directly.
Lorenz Bühmann
Lorenz Bühmann
6ee6fbd8b4b0d98ca0f572ec43bfee4b3e699f9c
Leo Obrst
Leo Obrst
Ricardo Pietrobon
Ricardo Pietrobon
df102e27188a2ad5ce28a421a2ea67124137e0e4
Evaluation measures for ontology matchers in supervised matching scenarios
Simplifying Description Logic Ontologies
Assisted Policy Management for SPARQL Endpoints Access Control
Assisted Policy Management for SPARQL Endpoints Access Control
Shi3ld is a context-aware authorization framework for protecting SPARQL endpoints. It assumes the definition of access policies using RDF and SPARQL, and the specification of named graphs to identify the protected resources. These assumptions lead to the incapability for users who are not familiar with such languages and technologies to use the authorization framework. In this paper, we present a graphical user interface to support dataset administrators to define access policies and the target elements protected by such policies.
Crowdsourcing Ontology Verification
Crowdsourcing Ontology Verification
As the scale and complexity of ontologies increases, so too do errors and engineering challenges. It is frequently unclear, however, to what degree extralogical ontology errors negatively affect the application that the ontology underpins. For example, “Shoe SubClassOf Foot” may be correct logically, but not in a human interpretation. Indeed, such errors, not caught by reasoning, are likely to be domain-specific, and thus identifying salient ontology errors requires consideration of the domain. There are both automated and manual methods that provide ontology quality assurance. Nevertheless, these methods do not readily scale as ontology size increases, and do not necessarily identify the most salient extralogical errors. Recently, crowdsourcing has enabled solutions to complex problems that computers alone cannot solve. For instance, human workers can quickly and more accurately identify objects in images at scale. Crowdsourcing presents an opportunity to develop methods for ontology quality assurance that overcome the current limitations of scalability and applicability. In this work, I aim (1) to determine the effect of extralogical ontology errors in an example domain, (2) to develop a scalable framework for crowdsourcing ontology verification that overcomes current ontology Q/A method limitations, and (3) to apply this framework to ontologies in use. I will then evaluate the method itself and also its effect in the context of a specific domain. As an example domain, I will use biomedicine, which applies many large-scale ontologies. Thus, this work will enable scalable quality assurance for extralogical errors in biomedical ontologies.
Kenny Zhu
Kenny Zhu
e928f0625ebcc1e8d690f28f58042a6bb0ec89a8
String Similarity Metrics for Ontology Alignment
Andreas Thor
Andreas Thor
Miguel Ceriani
Miguel Ceriani
9b74f6bd76efd758e9572a8906e6f8277eae6070
Interactive Pay as you go Relational-to-Ontology Mapping
Interactive Pay as you go Relational-to-Ontology Mapping
Ontology Based Data Access (OBDA) enables access to relational data with a complex structure through ontologies as conceptual domain models. To this end, mappings are required. A key aim of OBDA is to facilitate access to data with a complex structure. Ironically, though, in today’s existing OBDA systems mappings typically need to be compiled by hand, which is a complex and labor intensive task. Additionally, existing semi-automatic mapping approaches suffer from high human effort for cleaning up results. Fully automatic approaches, on the other side, suffer from a lack of precision and/or recall. In setups where the correctness of query results is crucial but the initial human effort must still be kept be small as possible, neither approach is acceptable. This situation calls for a guided, pay as you go feedback process for human mapping validation. We envision a comprehensive suite of methods and techniques that work well with one another in a seamless mapping process and support mapping construction in the context of OBDA. This suite will in part consist of a recombination and adaptation of various existing methods, but will also comprise newly devised algorithms and techniques.
Christoph Lange
Christoph Lange
Pieter Colpaert
Pieter Colpaert
513d030bd623fb5a5bb622d7ee66cf29a10c9340
OU Social: Reaching Students in Social Media
OU Social: Reaching Students in Social Media
This work describes OU Social, an application that collects and analyses data from public Facebook groups set up by students to discuss particular Open University courses. This application exploits semantic technologies to monitor the behaviour of users over time as well as the topics that emerge from Facebook group discussions. The paper describes the architecture of OU Social and provides a brief overview of the analysis results obtained from 44 different Facebook groups examined over a 6 year period (2007-2013)
Kalina Bontcheva
Kalina Bontcheva
University of Victoria
University of Victoria
Ollivier Haemmerlé
Ollivier Haemmerlé
d9de26a66d4d2e44bf5f4d1e843449e1b5dfeb54
Davide Picca
Davide Picca
What's in a 'nym'? Synonyms in Biomedical Ontology Matching
EPFL
EPFL
Mihaela Verman
Mihaela Verman
17c2be2488918cfb4a9110315c18c2ad85341dc2
Demonstration: Semantic Web Enabled Smart Farm with GSN
Demonstration: Semantic Web Enabled Smart Farm with GSN
GSN is an open source middleware for managing data produced by sensors deployed in a sensor network. We have extended and enhanced GSN to enable (i) semantically aware preparation, exchange and processing of the data (ii) user specified event processing for alerts and (iii) associate sensor data to 'things'. Here, we demonstrate our smart farm as a use case of a semantically aware sensor network for better integration of sensor data.
Peter Goodall
Peter Goodall
QODI: Query as Context in Automatic Data Integration
Free University of Bozen-Bolzano
Free University of Bozen-Bolzano
9th International Workshop on Uncertainty Reasoning for the Semantic Web
Legibility, Privacy and Creativity: Linked Data in a Surveillance Society
Legibility, Privacy and Creativity: Linked Data in a Surveillance Society
Blaž Fortuna
Blaž Fortuna
Explaining Clusters with Inductive Logic Programming and Linked Data
Explaining Clusters with Inductive Logic Programming and Linked Data
Knowledge Discovery consists in discovering hidden regulari- ties in large amount of data using data mining techniques. The obtained patterns require an interpretation that is usually achieved using some background knowledge given by experts from several domains. On the other hand, the rise of Linked Data has increased the number of con- nected cross-disciplinary knowledge, in the form of RDF datasets, classes and relationships. Here we show how Linked Data can be used in an Inductive Logic Programming process, where they provide background knowledge for finding hypotheses regarding the unrevealed connections between items of a cluster. By using an example with clusters of books, we show how different Linked Data sources can be used to automatically generate rules giving an underlying explanation to such clusters.
Alessio Palmero Aprosio
Alessio Palmero Aprosio
001e4d4a00b9bf4295967dcc0d3840c147704c63
Zhe Wu
Zhe Wu
Carole Goble
Carole Goble
4699824a3759895701ccaaa26c2ba7aaa5397b80
Manolis Koubarakis
Manolis Koubarakis
92ea611cf55f95a0ffd94eca818bb9d8a3f9a735
Collibra NV
Collibra NV
Exploring Scholarly Data with Rexplore
Exploring Scholarly Data with Rexplore
Despite the large number and variety of tools and services available today for exploring scholarly data, current support is still very limited in the context of sensemaking tasks, which go beyond standard search and ranking of authors and publications, and focus instead on i) understanding the dynamics of research areas, ii) relating authors ‘semantically’ (e.g., in terms of common interests or shared academic trajectories), or iii) performing fine-grained academic expert search along multiple dimensions. To address this gap we have developed a novel tool, Rexplore, which integrates statistical analysis, semantic technologies, and visual analytics to provide effective support for exploring and making sense of scholarly data. Here, we describe the main innovative elements of the tool and we present the results from a task-centric empirical evaluation, which shows that Rexplore is highly effective at providing support for the aforementioned sensemaking tasks. In addition, these results are robust both with respect to the background of the users (i.e., expert analysts vs. ‘ordinary’ users) and also with respect to whether the tasks are selected by the evaluators or proposed by the users themselves.
Hassan Saif
Hassan Saif
A case for transparency
A case for transparency
Axel Ngonga
Axel Ngonga
Andrew Terhorst
Andrew Terhorst
Serge Ter Braake
Serge Ter Braake
Getting Lucky in Ontology Search: A Data-Driven Evaluation Framework for Ontology Ranking
Getting Lucky in Ontology Search: A Data-Driven Evaluation Framework for Ontology Ranking
With hundreds, if not thousands, of ontologies available today in many different domains, ontology search and ranking has become an important and timely problem. When a user searches a collection of ontologies for her terms of interest, there are often dozens of ontologies that contain these terms. How does she know which ontology is the most relevant to her search? Our research group hosts BioPortal, a public repository of more than 330 ontologies in the biomedical domain. When a term that a user searches for is available in multiple ontologies, how do we rank the results and how do we measure how well our ranking works? In this paper, we develop an evaluation framework that enables developers to compare and analyze the performance of different ontology-ranking methods. Our framework is based on processing search logs and determining how often users select the top link that the search engine offers. We evaluate our framework by analyzing the data on BioPortal searches. We explore several different ranking algorithms and measure the effectiveness of each ranking by measuring how often users click on the highest ranked ontology. We collected log data from more than 4,800 BioPortal searches. Our results show that regardless of the ranking, in more than half the searches, users select the first link. Thus, it is even more critical to ensure that the ranking is appropriate if we want to have satisfied users. Our further analysis demonstrates that ranking ontologies based on page view data significantly improves the user experience, with an approximately 26% increase in the number of users who select the highest ranked ontology for the search.
Graße—Towards Flexible Search on Encrypted Graph Data
Graße—Towards Flexible Search on Encrypted Graph Data
Selver Softic
Selver Softic
b0501ce2c98e4629f4b60b13afa3b693f6829940
Paolo Ciancarini
Paolo Ciancarini
f2918e17b4b356eb9731b54b0fd710dbfede6681
Cássia Trojahn
Cássia Trojahn
University of Freiburg
University of Freiburg
Sépage
Sépage
Modelling Ontologies Visually Session 2
Gregor Leban
Gregor Leban
f9b3bde56dab00572b3768ec02e1a6c3d42dfdf3
Relational Database to RDF Session 3
FedSearch: efficiently combining structured queries and full-text search in a SPARQL federation
FedSearch: efficiently combining structured queries and full-text search in a SPARQL federation
Combining structured queries with full-text search provides a powerful means to access distributed linked data. However, executing hybrid search queries in a federation of multiple data sources presents a number of challenges due to data source heterogeneity and lack of statistical data about keyword selectivity. To address these challenges, we present FedSearch – a novel hybrid query engine based on the SPARQL federation framework FedX. We extend the SPARQL algebra to incorporate keyword search clauses as first-class citizens and apply novel optimization techniques to improve the query processing efficiency while maintaining a meaningful ranking of results. By performing on-the-fly adaptation of the query execution plan and intelligent grouping of query clauses, we are able to reduce significantly the communication costs making our approach suitable for top-k hybrid search across multiple data sources. In experiments we demonstrate that our optimization techniques can lead to a substantial performance improvement, reducing the execution time of hybrid queries by more than an order of magnitude.
Dan Brickley
Dan Brickley
Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web
Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web
Gregor Heinrich
Gregor Heinrich
Richard Hosking
Richard Hosking
08eada8f88cd6e002db77a61ec985da3798c5692
Nilam Prasai
Nilam Prasai
Personal Privacy and the Web of Linked Data
Personal Privacy and the Web of Linked Data
KAIST
KAIST
Marta Sabou
Marta Sabou
Davide Ceolin
Davide Ceolin
Yi Zhou
Yi Zhou
Relational Database to RDF Session 2
Event Processing in RDF
Event Processing in RDF
Simplifying Description Logic Ontologies
Simplifying Description Logic Ontologies
We discuss the problem of minimizing TBoxes expressed in the light-weight description logic E L, which forms a basis of some large ontologies like SNOMED, Gene Ontology, NCI and Galen. We show that the minimization of TBoxes is intractable (NP-complete). While this looks like a bad news result, we also provide a heuristic technique for minimizing TBoxes. We prove the correctness of the heuristics and show that it provides optimal results for a class of ontologies, which we define through an acyclicity constraint over a reference relation between equivalence classes of concepts. To establish the feasibility of our approach, we have implemented the algorithm and evaluated its effectiveness on a small suite of benchmarks.
Semantic Web Technologies for Social Translucence and Privacy Mirrors on the Web
Semantic Web Technologies for Social Translucence and Privacy Mirrors on the Web
Relational Database to RDF Session 1
ORCHID – Reduction-Ratio-Optimal Computation of Geo-Spatial Distances for Link Discovery
ORCHID – Reduction-Ratio-Optimal Computation of Geo-Spatial Distances for Link Discovery
The discovery of links between resources within knowledge bases is of crucial importance to realize the vision of the Semantic Web. Addressing this task is especially challenging when dealing with geo-spatial datasets due to their sheer size and the potential complexity of single geo-spatial objects. Yet, so far, little attention has been paid to the characteristics of geo-spatial data within the context of link discovery. In this paper, we address this gap by presenting Orchid, a reduction-ratio-optimal link discovery approach designed especially for geo-spatial data. Orchid relies on a combination of the Hausdorff and orthodromic metrics to compute the distance between geo-spatial objects. We first present two novel approaches for the efficient computation of Hausdorff distances. Then, we present the space tiling approach implemented by Orchid and prove that it is optimal with respect to the reduction ratio that it can achieve. The evaluation of our approaches is carried out on three real datasets of different size and complexity. Our results suggest that our approaches to the computation of Hausdorff distances require two orders of magnitude less orthodromic distances computations to compare geographical data. Moreover, they require two orders of magnitude less time than a naive approach to achieve this goal. Finally, our results indicate that Orchid scales to large datasets while outperforming the state of the art significantly.
Energy efficient sensing for managing privacy on smartphones
Energy efficient sensing for managing privacy on smartphones
Ahsan Morshed
Ahsan Morshed
A Rule-Based Relation Extraction System using DBpedia and Syntactic Parsing
Prabhaker Mateti
Prabhaker Mateti
Bringing Math to LOD: A Semantic Publishing Platform Prototype for Scientific Collections in Mathematics
Bringing Math to LOD: A Semantic Publishing Platform Prototype for Scientific Collections in Mathematics
We present our work on developing a software platform for mining mathematical scholarly papers to obtain a Linked Data representation. Currently, the Linking Open Data (LOD) cloud lacks up-to-date and detailed information on professional level mathematics. To our mind, the main reason for that is the absence of appropriate tools that could analyze the underlying semantics in mathematical papers and effectively build their consolidated representation. We have developed a holistic approach to analysis of mathematical documents, including ontology based extraction, conversion of the article body as well as its metadata into RDF, integration with some existing LOD data sets, and semantic search. We argue that the platform may be helpful for enriching user experience on modern online scientific collections.
Towards a Configurable Framework for Iterative Signing of Distributed Graph Data
Towards a Configurable Framework for Iterative Signing of Distributed Graph Data
A Checklist-Based Approach for Quality Assessment of Scientific Information
David Lamb
David Lamb
240a3dd06df5b9e8a494f7822441efdbc836aa84
Semantic Metadata for Music Production Projects
Deep-linking into Media Assets at the Fragment Level: Specification, Model and Applications
Kjetil Kjernsmo
Kjetil Kjernsmo
37184373f6d39505f39c65e3e62f309d4a5630f6
Semantic Message Passing for Generating Linked Data from Tables
Semantic Message Passing for Generating Linked Data from Tables
We describe work on automatically inferring the intended meaning of tables and representing it as RDF linked data, making it available for improving search, interoperability and integration. We present implementation details of a joint inference module that uses knowledge from the linked open data (LOD) cloud to jointly infer the semantics of column headers, table cell values (e.g., strings and numbers) and relations between columns. We also implement a novel Semantic Message Passing algorithm which uses LOD knowledge to improve existing message passing schemes. We evaluate our implemented techniques on tables from the Web and Wikipedia.
Ontology Patterns: Clarifying Concepts and Terminology
Ontology Patterns: Clarifying Concepts and Terminology
A Semantic Lab Notebook – Report on a Use Case Modelling an Experiment of a Microwave-based Quarantine Method
Luz Marina Alvare
Luz Marina Alvare
Mapping, Interlinking and Exposing MusicBrainz as Linked Data
A knowledge-based approach to computational analysis of melody in Indian art music
Anni-Yasmin Turhan
Anni-Yasmin Turhan
Terminology-Based Patterns for Natural Language Definitions in Ontologies
Terminology-Based Patterns for Natural Language Definitions in Ontologies
Semantic Rule Filtering for Web-Scale Relation Extraction
Semantic Rule Filtering for Web-Scale Relation Extraction
Web-scale relation extraction is a means for building and extending large repositories of formalized knowledge. This type of automated knowledge building requires a decent level of precision, which is hard to achieve with automatically acquired rule sets learned from unlabeled data by means of distant or minimal supervision. This paper shows how precision of relation extraction can be considerably improved by employing a wide-coverage, general-purpose lexical semantic network, i.e., BabelNet, for effective semantic rule filtering. We apply Word Sense Disambiguation to the content words of the automatically extracted rules. As a result a set of relation-specific relevant concepts is obtained, and each of these concepts is then used to represent the structured semantics of the corresponding relation. The resulting relation-specific subgraphs of BabelNet are used as semantic filters for estimating the adequacy of the extracted rules. For the seven semantic relations tested here, the semantic filter consistently yields a higher precision at any relative recall value in the high-recall range.
Albert Meroño-Peñuela
Albert Meroño-Peñuela
Berkant Barla Cambazoglu
Berkant Barla Cambazoglu
cf1c01c88f99d224cfbb34e545658b29a2b1e048
Technical University of Hamburg
Technical University of Hamburg
Reasoning Performance Indicators for Ontology Design Patterns
Reasoning Performance Indicators for Ontology Design Patterns
Jose Mora
Jose Mora
5079179141c321b8e6bfacb141ac71aca0cc22a3
A snapshot of the OWL Web
A snapshot of the OWL Web
Tool development for and empirical experimentation in OWL ontology engineering require a wide variety of suitable ontologies as input for testing and evaluation purposes and detailed characterisations of real ontologies. Empirical activities often resort to (somewhat arbitrarily) hand curated corpora available on the web, such as the NCBO BioPortal and the TONES Repository, or manually selected sets of well-known ontologies. Findings of surveys and results of benchmarking activities may be biased, even heavily, towards these datasets. Sampling from a large corpus of ontologies, on the other hand, may lead to more representative results. Current large scale repositories and web crawls are mostly uncurated and suffer from duplication, small and (for many purposes) uninteresting ontology files, and contain large numbers of ontology versions, variants, and facets, and therefore do not lend themselves to random sampling. In this paper, we survey ontologies as they exist on the web and describe the creation of a corpus of OWL DL ontologies using strategies such as web crawling, various forms of de-duplications and manual cleaning, which allows random sampling of ontologies for a variety of empirical applications.
Luca Costabello
Luca Costabello
2a8ce9a87fb5a19cf4a86a84b7fab221e4e4b2b2
Mathias Niepert
Mathias Niepert
Modelling Ontologies Visually Session 1
Using Semantic Web Technologies to Reproduce a Pharmacovigilance Case Study
Heiko Paulheim
Heiko Paulheim
8fe63debbbaf9daa6d4def3ebfdf5e0d6ac2d368
María Poveda-Villalón
María Poveda-Villalón
Discussion / Hack ideas for the ISWC jam session
Saemi Jang
Saemi Jang
e54905988467d86d06f6f08ebcd9a8292a9d3f83
Introduction
David Camilo Corrales
David Camilo Corrales
The Combined Approach to OBDA: Taming Role Hierarchies using Filters
The Combined Approach to OBDA: Taming Role Hierarchies using Filters
The basic idea of the combined approach to query answering in the presence of ontologies is to materialize the consequences of the ontology in the data and then use a limited form of query rewriting to deal with infinite materializations. While this approach is efficient and scalable for ontologies that are formulated in the basic version of the description logic DL-Lite, it incurs an exponential blowup during query rewriting when DL-Lite is extended with the popular role hierarchies. In this paper, we show how to replace the query rewriting with a filtering technique. This is natural from an implementation perspective and allows us to handle role hierarchies without an exponential blowup. We also carry out an experimental evaluation that demonstrates the scalability of this approach.
Statistical Knowledge Patterns for Characterising Linked Data
Statistical Knowledge Patterns for Characterising Linked Data
Salzburg Research
Salzburg Research
Relational Database to RDF Session 4
Alistair Sackley
Alistair Sackley
Guadalupe Aguado
Guadalupe Aguado
A decision procedure for SHOIQ with transitive closure of roles
United States Army Research Laboratory
United States Army Research Laboratory
DAW: Duplicate-AWare Federated Query Processing over the Web of Data
Albert Zündorf
Albert Zündorf
Data Access
Towards an automatic creation of localized versions of DBpedia
Towards an automatic creation of localized versions of DBpedia
DBpedia is a large-scale knowledge base that exploits Wikipedia as primary data source. The extraction procedure requires to manually map Wikipedia infoboxes into the DBpedia ontology. Thanks to crowdsourcing, a large number of infoboxes has been mapped in the English DBpedia. Consequently, the same procedure has been applied to other languages to create the localized versions of DBpedia. However, the number of accomplished mappings is still small and limited to most frequent infoboxes. Furthermore, mappings need maintenance due to the constant and quick changes of Wikipedia articles. In this paper, we focus on the problem of automatically mapping infobox attributes to properties into the DBpedia ontology for extending the coverage of the existing localized versions or building from scratch versions for languages not covered in the current version. The evaluation has been performed on the Italian mappings. We compared our results with the current mappings on a random sample re-annotated by the authors. We report results comparable to the ones obtained by a human annotator in term of precision, but our approach leads to a significant improvement in recall and speed. Specifically, we mapped 45,978 Wikipedia infobox attributes to DBpedia properties in 14 different languages for which mappings were not yet available. The resource is made available in an open format.
FRED as an Event Extraction Tool
FRED as an Event Extraction Tool
Wikimedia Deutschland
Wikimedia Deutschland
CSIRO Australia
CSIRO Australia
Kunal Sengupta
Kunal Sengupta
c8f4c0d4ae0a9e2584fa542b99feaa20eed99f29
6d12565dc6da5a07d44bf05bc0023a604ccc5a6d
Empirical Study of Logic-Based Modules: Cheap Is Cheerful
George Mason University
George Mason University
Towards a systematic benchmarking of ontology-based query rewriting systems
Birzeit University
Birzeit University
Knowledge Extraction
Personalized Best Answer Computation in Graph Databases
Personalized Best Answer Computation in Graph Databases
Though subgraph matching has been extensively studied as a query paradigm in semantic web and social network data environments, a user can get a large number of answers in response to a query. Just like Google does, these answers can be shown to the user in accordance with an importance ranking. In this paper, we present scalable algorithms to find the top-K answers to a practically important subset of SPARQL-queries, denoted as importance queries, via a suite of pruning techniques. We test our algorithms on multiple real-world graph data sets, showing that our algorithms are efficient even on networks with up to 6M vertices and 15M edges and far more efficient than popular triple stores.
Representing Supply Chain Events on the Web of Data
Representing Supply Chain Events on the Web of Data
Elisabetta Di Nitto
Elisabetta Di Nitto
Jarrod Trevathan
Jarrod Trevathan
Zohra Bellahsene
Zohra Bellahsene
Feiyu Xu
Feiyu Xu
fccc02a7021a0deb0e5a9a3d4081550fafa38bf4
University of Hasselt
University of Hasselt
V.S. Subrahmanian
V.S. Subrahmanian
Unchained Melody: Redefining the Boundaries to a Music Digital Library Through Linked Data
Philippe Cudré-Mauroux
Philippe Cudré-Mauroux
cd093dfee55f5ac86ec10c79157bff2ad1107ec9
c75b819eaa9783d69c88512d2ddac7b2a4cb60a8
New York University
New York University
Rensselaer Polytechnic Institute
Rensselaer Polytechnic Institute
Personalized Best Answer Computation in Graph Databases
Linked Data 2
Gopala Krishna Koduri
Gopala Krishna Koduri
Krishna Sinha
Krishna Sinha
Olga Nevzorova
Olga Nevzorova
9718dbbfc46f06e02cd948e226bdc94a0f9404f4
Linked Open Data and its applications for International development: The case study at International Food Policy Research Institute
Linked Open Data and its applications for International development: The case study at International Food Policy Research Institute
Niels Ockeloen
Niels Ockeloen
University of Lisbon
University of Lisbon
INRIA Sophia Antipolis
INRIA Sophia Antipolis
Karen Karapetyan
Karen Karapetyan
6bc28d543095d324986abfdb7383101f5312eb5b
Michael Mecham
Michael Mecham
Controlled Query Evaluation over OWL 2 RL Ontologies
Domain-Independent Quality Measures for Crowd Truth Disagreement
Domain-Independent Quality Measures for Crowd Truth Disagreement
Yahoo!
Yahoo!
Evaluation Track
Opportunities created for agricultural and environmental informatics through whole-of-economy federated sensing
Opportunities created for agricultural and environmental informatics through whole-of-economy federated sensing
Matteo Palmonari
Matteo Palmonari
08c7efb2d512787826a79444381b679167134bb4
Kazan (Volga region) Federal University
Kazan (Volga region) Federal University
Soon Gill Hong
Soon Gill Hong
6bb0029fb62a26c7c9c1f585124a0496bc7879b2
Detecting and Reporting Extensional Concept Drift in Statistical Linked Data
George Fazekas
George Fazekas
Capsenta Inc
Capsenta Inc
Olaf Hartig
Olaf Hartig
Figene Ahmedi
Figene Ahmedi
Vincenzo Maltese
Vincenzo Maltese
AgroKnowledgeBase (AKB) for plant diseases: Poppy plant use case
AgroKnowledgeBase (AKB) for plant diseases: Poppy plant use case
Paul Buitelaar
Paul Buitelaar
Papers selected for the data challenge
Google Inc.
Google Inc.
Krzysztof Janowicz
Krzysztof Janowicz
a09448c2b7c9d3d4d56b2a11c7dee3a2aee7c289
Connected Discovery & OpenPHACTS
Connected Discovery & OpenPHACTS
Mark Sanderson
Mark Sanderson
Brendan Ashby
Brendan Ashby
732f9968fe6080454ddeecfeb345224afcabc675
Part I. Definitions and State of the Market
Hui Lin
Hui Lin
The role of vocabularies for estimating carbon footprint for food recipies using Linked Open Data
The role of vocabularies for estimating carbon footprint for food recipies using Linked Open Data
Extractivism: Extracting activist events from news articles using existing NLP tools and services
Extractivism: Extracting activist events from news articles using existing NLP tools and services
Announcement of the challenge winner
Yuan Ni
Yuan Ni
Raj Gaire
Raj Gaire
559367f84fcbb11a308c183b3d839925bd03bb45
Olaf Görlitz
Olaf Görlitz
Danh Le Phuoc
Danh Le Phuoc
ISWC 2013 Doctoral Consortium
Early warning system for coffee rust disease based on error correcting output codes: a proposal
Early warning system for coffee rust disease based on error correcting output codes: a proposal
Charalampos Nikolaou
Charalampos Nikolaou
d6aff7cc4a58c5d21d04ab22d4faa7bd2bdb00bf
A case study on automated risk assessment of ships using newspaper-based event extraction
A case study on automated risk assessment of ships using newspaper-based event extraction
Part II. Big Data Algorithms
DISI – Universita ́ degli Studi di Trento
DISI – Universita ́ degli Studi di Trento
Chan Le Duc
Chan Le Duc
833d318a688a62e62c04f6b9b95776a1f0a929d0
Simone Paolo Ponzetto
Simone Paolo Ponzetto
Triplifying Wikipedia's Tables
Triplifying Wikipedia's Tables
Rafael Mezzomo de Souza
Rafael Mezzomo de Souza
Luciano Serafini
Luciano Serafini
7fea00a39da1a3986831556109303fc904b9f935
A Role for Provenance in Social Computation
A Role for Provenance in Social Computation
University of Montpellier
University of Montpellier
Linked Open Robot Data
Linked Open Robot Data
Order Theoretical Semantic Recommendation
Order Theoretical Semantic Recommendation
Kasjen Kraemer
Kasjen Kraemer
3907347bc666b4456d811af8339c180a4242d486
Danilo Ardagna
Danilo Ardagna
Aston University
Aston University
Stefan Senger
Stefan Senger
5acced9dfbb15990291a5de1feff8a3c5f526d38
University of London
University of London
Track 1
Tutorial 8: Big Data Management
Hideaki Takeda
Hideaki Takeda
Giseli Rabello Lopes
Giseli Rabello Lopes
3944238928677e2886e319930c7fd93140f4bc8c
Linked Data for Cross-disciplinary Collaboration Cohort Discovery
Linked Data for Cross-disciplinary Collaboration Cohort Discovery
Andrea Moro
Andrea Moro
79c4dd813df586471940dfb64c53a7216cd3ebde
Crowdsourced Entity Markup
Crowdsourced Entity Markup
IBM Ireland Research Laboratory
IBM Ireland Research Laboratory
SPARQL Update under RDFS Entailment in Fully Materialized and Redundancy-Free Triple Stores
SPARQL Update under RDFS Entailment in Fully Materialized and Redundancy-Free Triple Stores
Richard Cyganiak
Richard Cyganiak
Semantic Web Enabled Smart Farming
Semantic Web Enabled Smart Farming
Austrian Environmental Data Consumption – A Mashup-based Approach
Austrian Environmental Data Consumption – A Mashup-based Approach
Nanjing University
Nanjing University
Bernardo Cuenca Grau
Bernardo Cuenca Grau
c0879a5783f8750335b2d2830dd7dbb99dc8f94b
Marut Buranarach
Marut Buranarach
Full Syntactic Parsing for Enrichment of RDF dataset
Full Syntactic Parsing for Enrichment of RDF dataset
György Fazekas
György Fazekas
SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing
SLUA: Towards Semantic Linking of Users with Actions in Crowdsourcing
Felix Leif Keppmann
Felix Leif Keppmann
835970126b67a01dab338ba986940c35f44edaee
Learning Classifiers from Semantic Sensor Data with Application to Soil Drainage Classification
Learning Classifiers from Semantic Sensor Data with Application to Soil Drainage Classification
Laurent Pierre
Laurent Pierre
9c6a3e8bf33ffb595d60683c2f10d71583cb593e
Dean Allemang
Dean Allemang
Hugh Glaser
Hugh Glaser
Crowdsourced Semantics with Semantic Tagging: Don’t just tag it, LexiTag it!
Crowdsourced Semantics with Semantic Tagging: Don’t just tag it, LexiTag it!
Which of the following SPARQL Queries are Similar? Why?
Which of the following SPARQL Queries are Similar? Why?
Andrew Woolf
Andrew Woolf
Extending SPARQL with Qualitative Preferences
Extending SPARQL with Qualitative Preferences
Lorenzino Vaccari
Lorenzino Vaccari
Yarmouk University
Yarmouk University
Femke Ongenae
Femke Ongenae
c979080c0d162570600ee44eed83bfe0fe9c69b6
Yanan Zhang
Yanan Zhang
f57c6ce0be1847b1f903eff48929726bc56a47de
René Witte
René Witte
Thomas Wilmering
Thomas Wilmering
Universidade Nova de Lisboa
Universidade Nova de Lisboa
Named Entity Disambiguation using Freebase and Syntactic Parsing
Named Entity Disambiguation using Freebase and Syntactic Parsing
Dr. Detective: combining gamification techniques and crowdsourcing to create a gold standard in medical text
Dr. Detective: combining gamification techniques and crowdsourcing to create a gold standard in medical text
National University of Ireland, Galway
National University of Ireland, Galway
Frederik Armknecht
Frederik Armknecht
Tutorial 4: Modelling Ontologies Visually
RDFChain: Chain Centric Storage for Scalable Join Processing of RDF Graphs using MapReduce and HBase
RDFChain: Chain Centric Storage for Scalable Join Processing of RDF Graphs using MapReduce and HBase
As a massive linked open data is available in RDF, the scalable storage and efficient retrieval using MapReduce have been actively studied. Most of previous researches focus on reducing the number of MapReduce jobs for processing join operations in SPARQL queries. However, the cost of shuffle phase still occurs due to their reduce-side joins. In this paper, we propose RDFChain which supports the scalable storage and efficient retrieval of a large volume of RDF data using a combination of MapReduce and HBase which is NoSQL storage system. Since the proposed storage schema of RDFChain reflects all the possible join patterns of queries, it provides a reduced number of storage accesses depending on the join pattern of a query. In addition, the proposed cost-based map-side join of RDFChain reduces the number of map jobs since it processes as many joins as possible in a map job using statistics.
Sebastian Krause
Sebastian Krause
c47cf68971d68146ed0b1f7f382926f287fd8de5
University of Edinburgh
University of Edinburgh
Danica Damljanovic
Danica Damljanovic
Shanghai Jiao Tong University
Shanghai Jiao Tong University
Anthony Levas
Anthony Levas
Vanessa Lopez
Vanessa Lopez
5c3ac25297fd6033d663d292004b1e8d977ceb5f
ActiveRaUL: A Web form-based User Interface to create and maintain RDF data
ActiveRaUL: A Web form-based User Interface to create and maintain RDF data
With the advent of Linked Data the amount of automatically generated machine-readable data on the Web, often obtained by means of mapping relational data to RDF, has risen significantly. However, manually created, quality-assured and crowd-sourced data based on ontologies, is not available in the quantities that would realise the full potential of the semantic Web. One of the barriers for semantic Web novices to create machine-readable data, is the lack of easy-to-use Web publishing tools that separate the schema modelling from the data creation. In this demonstration we present ActiveRaUL, a Web service that supports the automatic generation of Web form-based user interfaces from any input ontology. The resulting Web forms are unique in supporting users, inexperienced in semantic Web technologies, to create and maintain RDF data modelled according to an ontology. We report on a use case based on the Sensor Network Ontology that supports the viability of our approach.
Tutorial 5: Microtask crowdsourcing to solve Semantic Web problems
Greg Timms
Greg Timms
Boris Villazón-Terrazas
Boris Villazón-Terrazas
Yves Jaques
Yves Jaques
XLore: A Large-scale English-Chinese Bilingual Knowledge Graph
XLore: A Large-scale English-Chinese Bilingual Knowledge Graph
Current Wikipedia-based multilingual knowledge bases still suffer the following problems: (i) the scarcity of non-English knowledge, (ii) the noise in the semantic relations and (iii) the limited coverage of equivalent cross-lingual entities. In this demo, we present a large-scale bilingual knowledge graph named XLore, which has adequately solved the above problems.
Tutorial 9: Linked Data for Web Scale Information Extraction
IJS
IJS
Track 3
Tom De Nies
Tom De Nies
c96075b326e3cd7a080c63b70f0832522c65ac4c
University of Rennes 1
University of Rennes 1
Paolo Ciccarese
Paolo Ciccarese
Armin Haller
Armin Haller
00469ffc86d1f96c0144a4028e60566dadd7da47
PreviousNext
PreviousNext
IBM China Research Laboratory
IBM China Research Laboratory
Siegfried Handschuh
Siegfried Handschuh
Track 2
Borislav Popov
Borislav Popov
Tutorial 7: Hands-on Guide to Linked Data Applications
Git2PROV: Exposing Version Control System Content as W3C PROV
Git2PROV: Exposing Version Control System Content as W3C PROV
Data provenance is defined as information about entities, activities and people producing or modifying a piece of data. On the Web, the interchange of standardized provenance of (linked) data is an essential step towards establishing trust. One mechanism to track (part of) the provenance of data, is through the use of version control systems (VCS), such as Git. These systems are widely used to facilitate collaboration primarily for both code and data. Here, we describe a system to expose the provenance stored in VCS in a new standard Web-native format: W3C PROV. This enables the easy publication of VCS provenance on the Web and subsequent integration with other systems that make use of PROV. The system is exposed as a RESTful Web service, which allows integration into user-friendly tools, such as browser plugins.
Egon Willighagen
Egon Willighagen
17d767fcc2310ff14ad8702a75f6f00e18214aec
Manfred Overmeen
Manfred Overmeen
Bernhard Schandl
Bernhard Schandl
Tutorial 3: The Web of Things
Using the past to explain the present: interlinking current affairs with archives via the Semantic Web
Industry 1
A Distributed Reasoning Platform to Preserve Energy in Wireless Sensor Networks
A Distributed Reasoning Platform to Preserve Energy in Wireless Sensor Networks
A distributed reasoning platform is presented to reduce the energy consumption of Wireless Sensor Networks (WSNs) offering geospatial services by minimizing the amount of wireless communication. It combines local, rule-based reasoning on the sensors and gateways with global, ontology-based reasoning on the back-end servers. The Semantic Sensor Network (SNN) Ontology was extended to model the WSN energy consumption. Two prototypes are presented: the Personal Parking Assistant (PPA) and Garbage Bin Tampering Monitor (GBTM).
Towards a Vocabulary for Incorporating Predictive Models into the Linked Data Web
A Graph-Based Approach to Learn Semantic Descriptions of Data Sources
Tutorial 6: The Mobile Semantic Web
Abir Qasem
Abir Qasem
Reasoning
Jerven Bolleman
Jerven Bolleman
University of Queensland
University of Queensland
OLAP Manipulations on RDF Data following a Constellation Model
Interlinking Multilingual LOD Resources: A Study on Connecting Chinese, Japanese, and Korean Resources Using the Unihan Database
Interlinking Multilingual LOD Resources: A Study on Connecting Chinese, Japanese, and Korean Resources Using the Unihan Database
This study proposes a novel method with which Chinese, Japanese, and Korean (CJK) resources on the Web can be effectively matched and connected. The three countries share Chinese characters even though Japan and Korea have their own language. Utilizing the Unihan database, which covers more than 45,000 characters commonly used by the three countries, we show that the proposed method outperforms the traditional method based on string matching in finding similar characters and words used in these countries. The results represent a first step towards overcoming the multilingual barrier in semantically interlinking Asian LOD resources.
DataPop, Inc.
DataPop, Inc.
Bundeswehr University Munich
Bundeswehr University Munich
Noseong Park
Noseong Park
6th International Workshop on Semantic Sensor Networks
Tutorial 2: Stream Reasoning for Linked Data
A Semantic Approach to Data Center Management
A Semantic Approach to Data Center Management
Finite Models in RDF(S), with datatypes
Finite Models in RDF(S), with datatypes
The details of reasoning in RDF are generally well known. The model-theoretic characteristcs of RDF have been less studied, particularly when datatypes are added. RDF reasoning can be performed by only considering finite models or pre-models, and sometimes only very small models need be considered.
Semantic Web Landscape
Esko Nuutila
Esko Nuutila
Fabio Ciravegna
Fabio Ciravegna
45182d8ef3aad3fc00e86c0dba37ac387c287dbb
David A. Shamma
David A. Shamma
Enrico Motta
Enrico Motta
c372d74601560f8655a90480e2eaddb69120af34
28a0f82609671f47d811e6bee865afb23abfb8db
Jožef Stefan Institute
Jožef Stefan Institute
Indiana University
Indiana University
Tutorial 1: Relational Database to RDF (RDB2RDF)
Xingjian Zhang
Xingjian Zhang
a50f4191e3e209b66518184da03845c8a3a4a475
Jane Hunter
Jane Hunter
aa9c9fb37fb8139e785ea9a59e2a8cc8cacf896e
Pierre-Antoine Champin
Pierre-Antoine Champin
Lydia Pintscher
Lydia Pintscher
Alessandro Mosca
Alessandro Mosca
56bffa11def8dee9df0b73fbae04023d3e85c5c3
Extending R2RML to a source-independent mapping language for RDF
Extending R2RML to a source-independent mapping language for RDF
Although reaching the fifth star of the Open Data deployment scheme demands the data to be represented in RDF and linked, a generic and standard mapping procedure to deploy raw data in RDF was not established so far. Only the R2RML mapping language was standardized but its applicability is limited to mappings from relational databases to RDF. We propose the extension of R2RML to also support mappings of data sources in other structured formats. Broadening its scope, the focus is put on the mappings and their optimal reuse. The language becomes source-agnostic, and resources are integrated and interlinked at a primary stage.
Rave Harpaz
Rave Harpaz
9c88b0772ccc79126dcd63e583de9567ca691e92
SLUBM: An extented LUBM Benchmark for Stream Reasoning
SLUBM: An extented LUBM Benchmark for Stream Reasoning
A Linked-Data-driven and Semantically-enabled Journal Portal for Scientometrics
Towards Constructive Evidence of Data Flow-oriented Web Service Composition
Towards Constructive Evidence of Data Flow-oriented Web Service Composition
Automation of service composition is one of the most interesting challenges facing the Semantic Web and the Web of services today. Despite approaches which are able to infer a partial order of services, its data flow remains implicit and difficult to be automatically generated. Enhanced with formal representations, the semantic links between output and input parameters of services can be then exploited to infer their data flow. This work addresses the problem of effectively inferring data flow between services based on their representations. To this end, we introduce the non standard Description Logic reasoning join, aiming to provide a “constructive evidence” of why services can be connected and how non trivial links (many to many parameters) can be inferred in data flow. The preliminary evaluation provides evidence in favor of our approach regarding the completeness of data flow.
IBM
IBM
Johannes Kepler University of Linz
Johannes Kepler University of Linz
Trevor Martin
Trevor Martin
Simón Bolívar University
Simón Bolívar University
KbQAS: A Knowledge-based QA System
KbQAS: A Knowledge-based QA System
In this demo paper, we present the first ontology-based Vietnamese question answeringsystem KbQAS in which a knowledge acquisition approach for question analysis is integrated.
Guillermo Soberon
Guillermo Soberon
Stephan Seufert
Stephan Seufert
21abce4ca132738b40ed4a84b1a44f74c0b95c47
John Nelson
John Nelson
cc9382d6562c7c967259236f6261a652f2ade735
Coffee break
Université Paris-Est, LIGM
Université Paris-Est, LIGM
Elastic and scalable processing of Linked Stream Data in the Cloud
Elastic and scalable processing of Linked Stream Data in the Cloud
Linked Stream Data extends the Linked Data paradigm to dynamic data sources. It enables the integration and joint processing of heterogeneous stream data with quasi-static data from the Linked Data Cloud in near-real-time. Several Linked Stream Data processing engines exist but their scalability still needs to be in improved in terms of (static and dynamic) data sizes, number of concurrent queries, stream update frequencies, etc. So far, none of them supports parallel processing in the Cloud, i.e., elastic load profiles in a hosted environment. To remedy these limitations, this paper presents an approach for elastically parallelizing the continuous execution of queries over Linked Stream Data. For this, we have developed novel, highly efficient, and scalable parallel algorithms for continuous query operators. Our approach and algorithms are implemented in our CQELS Cloud system and we present extensive evaluations of their superior performance on Amazon EC2 demonstrating their high scalability and excellent elasticity in a real deployment.
Stream Reasoning for Linked Data Session 1
TRank: Ranking Entity Types Using the Web of Data
PigSPARQL: A SPARQL Query Processing Baseline for Big Data
PigSPARQL: A SPARQL Query Processing Baseline for Big Data
In this paper, we discuss PigSPARQL, a competitive, yet easy to use, SPARQL query processing system based on MapReduce and thus intended for Big Data applications. Instead of a direct mapping, PigSPARQL uses the query language of Pig, a data analysis platform on top of Hadoop, as an intermediate layer between SPARQL and MapReduce. The additional level of abstraction makes our approach independent of the actual Hadoop version. Thus, it is automatically compatible to future changes of the Hadoop framework as they will be neutralized by the Pig layer and allows ad-hoc SPARQL query processing on large RDF graphs out of the box. In the paper we first revisit PigSPARQL and demonstrate PigSPARQL's gain of efficiency simply because switching from version Pig 0.5.0 to Pig 0.11.0. Because of this sustainability, PigSPARQL is an attractive long-term baseline for comparing various MapReduce based SPARQL implementations. This is underlined by PigSPARQL's competitiveness with existing systems, e.g. HadoopRDF.
Tania Tudorache
Tania Tudorache
638d023ba44fb531a81881698239ebb410af4790
Christian Meilicke
Christian Meilicke
aa10dcc1abe225b12ac6c62c75224109957f8837
Exploiting Stream Reasoning to Monitor multi-Cloud Applications
Exploiting Stream Reasoning to Monitor multi-Cloud Applications
Trinity College, Dublin
Trinity College, Dublin
A decision procedure for SHOIQ with transitive closure of roles
A decision procedure for SHOIQ with transitive closure of roles
The Semantic Web makes an extensive use of the OWL DL ontology language, underlied by the SHOIQ description logic, to formalize its resources. In this paper, we propose a decision procedure for this logic extended with the transitive closure of roles in concept axioms, a feature needed in several application domains. The most challenging issue we have to deal with when designing such a decision procedure is to represent infinitely non-tree-shaped models, which are different from those of SHOIQ ontologies. To address this issue, we introduce a new blocking condition for characterizing models which may have an infinite non-tree-shaped part.
José Luis Redondo-García
José Luis Redondo-García
Thomas Schneider
Thomas Schneider
aa02b685fee89355cabdce32fcf5c06983f8f671
Samhaa R. El-Beltagy
Samhaa R. El-Beltagy
Discovering Related Data Sources in Data-Portals
Matthias Klusch
Matthias Klusch
Discoverability of SPARQL Endpoints in Linked Open Data
Discoverability of SPARQL Endpoints in Linked Open Data
Accessing Linked Open Data sources with query languages such as SPARQL provides more flexible possibilities than access based on derefencerable URIs only. However, discovering a SPARQL endpoint on the fly, given a URI, is not trivial. This paper provides a quantitative analysis on the automatic discoverability of SPARQL endpoints using different mechanisms.
Thammasat University
Thammasat University
Willem Robert Van Hage
Willem Robert Van Hage
8985bbc3abd3830d25e6ed541b7bb1942eb85c27
Evaluating and benchmarking SPARQL query containment solvers
Sebastian Hellmann
Sebastian Hellmann
3b9b030bfa83b9c747d525b7943829d3abc2813b
Wan Fokkink
Wan Fokkink
Stefan Zwicklbauer
Stefan Zwicklbauer
8e420a3c1c6969b803d4bdf17afe78ae485a76fe
Event Object Boundaries in RDF Streams: A Position Paper
Event Object Boundaries in RDF Streams: A Position Paper
Secure Manipulation of Linked Data
Secure Manipulation of Linked Data
When it comes to publishing data on the web, the level of access control required (if any) is highly dependent on the type of content exposed. Up until now RDF data publishers have focused on exposing and linking public data. With the advent of SPARQL 1.1, the linked data infrastructure can be used, not only as a means of publishing open data but also, as a general mechanism for managing distributed graph data. However, such a decentralised architecture brings with it a number of additional challenges with respect to both data security and integrity. In this paper, we propose a general authorisation framework that can be used to deliver dynamic query results based on user credentials and to cater for the secure manipulation of linked data. Specifically we describe how graph patterns, propagation rules, conflict resolution policies and integrity constraints can together be used to specify and enforce consistent access control policies.
Introduction and motivation
Diego Calvanese
Diego Calvanese
Ivan Herman
Ivan Herman
Profiling of Linked Datasets using Structured Descriptions
Profiling of Linked Datasets using Structured Descriptions
While there exists an increasingly large number of Linked Data, metadata about the content covered by individual datasets is sparse. In this paper, we introduce a processing pipeline to automatically assess, annotate and index available linked datasets. Given a minimal description of a dataset from the DataHub, the process produces a structured RDF-based description that includes information about its main topics. Additionally, the generated descriptions embed datasets into an interlinked graph of datasets based on shared topic vocabularies. We adopt and integrate techniques for Named Entity Recognition and automated data validation, providing a consistent workflow for dataset profiling and annotation. Finally, we validate the results obtained with our tool.
Towards Linked Statistical Data Analysis
Introducing Statistical Design of Experiments to SPARQL Endpoint Evaluation
Integrating Relational Databases with the Semantic Web: Four Scenarios
Wikidata
Wikidata
Martin Stephenson
Martin Stephenson
90498c471a6ce3976f8c5413c586e5dab69a2a20
Stream Reasoning for Linked Data Session 4
Gangemi
Aldo Gangemi
8d7f004803b48a3b7c5e9f73dc16953069a6632d
Aldo
Aldo Gangemi
Aldo Gangemi
The Open University
The Open University
Incremental Reasoning in OWL EL without Bookkeeping
Incremental Reasoning in OWL EL without Bookkeeping
We describe a method for updating the classification of ontologies expressed in the E L family of Description Logics after some axioms have been added or deleted. While incremental classification modulo additions is relatively straightforward, handling deletions is more problematic since it requires retracting logical consequences that are no longer valid. Known algorithms address this problem using various forms of bookkeeping to trace the consequences back to premises. But such additional data can consume memory and place an extra burden on the reasoner during application of inferences. In this paper, we present a technique, which avoids this extra cost while being very efficient for small incremental changes in ontologies. The technique is freely available as a part of the open-source E L reasoner ELK and its efficiency is demonstrated on naturally occurring and synthetic data.
Helena Deus
Helena Deus
05802f3fcdc2725b2424297a45998bb5f9b13286
Linked Data for Web Scale Information Extraction Session 1
Goethe University Frankfurt
Goethe University Frankfurt
Gnowsis
Gnowsis
Dataset about iswc2013.
Tue May 03 19:01:41 CEST 2016
A Query Tool for EL with Non-monotonic rules
A Query Tool for EL with Non-monotonic rules
We present the Protégé plug-in NoHR that allows the user to take an E L+⊥ ontology, add a set of non-monotonic (logic programming) rules – suitable e.g. to express defaults and exceptions – and query the combined knowledge base. Our approach uses the well-founded semantics for MKNF knowledge bases as underlying formalism, so no restriction other than DL-safety is imposed on the rules that can be written. The tool itself builds on the procedure SLG(O) and, with the help of OWL 2 EL reasoner ELK, pre-processes the ontology into rules, whose result together with the non-monotonic rules serve as input for the topdown querying engine XSB Prolog. With the resulting plug-in, even queries to very large ontologies, such as SNOMED CT, augmented with a large number of rules, can be processed at an interactive response time after one initial brief pre-processing period. At the same time, our system is able to deal with possible inconsistencies between the rules and an ontology that alone is consistent.
Krishnaprasad Thirunarayan
Krishnaprasad Thirunarayan
Peter Chapman
Peter Chapman
Speaker Panel
Lunch
Stream Reasoning for Linked Data Session 2
Simplified OWL Ontology Editing for the Web: Is WebProtégé Enough?
Simplified OWL Ontology Editing for the Web: Is WebProtégé Enough?
Ontology engineering is a task that is notorious for its difficulty. As the group that developed Protégé, the most widely used ontology editor, we are keenly aware of how difficult the users perceive this task to be. In this paper, we present the new version of WebProtégé that we designed with two main goals in mind: (1) create a tool that will be easy to use while still accounting for commonly used OWL constructs; (2) support collaboration and social interaction around distributed ontology editing as part of the core tool design. We designed this new version of the WebProtégé user interface empirically, by analysing the use of OWL constructs in a large corpus of publicly available ontologies. Since the beta release of this new WebProtégé interface in January 2013, our users from around the world have created and uploaded 519 ontologies on our server. In this paper, we describe the key features of the new tool and our empirical design approach. We evaluate language coverage in WebProtégé by assessing how well it covers the OWL constructs that are present in ontologies that users have uploaded to WebProtégé. We evaluate the usability of WebProtégé through a usability survey. Our analysis validates our empirical design, suggests additional language constructors to explore, and demonstrates that an easy-to-use web-based tool that covers most of the frequently used OWL constructs is sufficient for many users to start editing their ontologies.
University of Birmingham
University of Birmingham
Animesh Manglik
Animesh Manglik
08094cb74ae7afc0065ce578e3622a7152c17368
University of Milan
University of Milan
Elena Montiel Ponsoda
Elena Montiel Ponsoda
Coffee break
OData and the Semantic Web
Marcin Wylot
Marcin Wylot
6ce7f01f8f5c35e75b7868ba851b5092d2896b50
Diana Maynard
Diana Maynard
Stream Reasoning for Linked Data Session 3
ProSWIP: Property-based Data Access for Semantic Web Interactive Programming
ProSWIP: Property-based Data Access for Semantic Web Interactive Programming
The Semantic Web has matured from a mere theoretical vision to a variety of ready-to-use linked open data sources currently available on the Web. Still, with respect to application development , the Web community is just starting to develop new paradigms in which data as the main driver of applications is promoted to first class status. Relying on properties of resources as an indicator for the type, property-based typing is such a paradigm. In this paper, we inspect the feasibility of property-based typing for accessing data from the linked open data cloud. Problems in terms of transparency and quality of the selected data were noticeable. To alleviate these problems, we developed an iterative approach that builds on human feedback.
Wright State University
Wright State University
PeerIndex
PeerIndex
Jooik Jung
Jooik Jung
2d5620c54c5a7a5add5d943131bd53bc99bc0097
Lynda Hardman
Lynda Hardman
Nuance Communications
Nuance Communications
École Nationale Supérieure des Mines de Saint-Étienne
École Nationale Supérieure des Mines de Saint-Étienne
Max Wilson
Max Wilson
Alberto Lavelli
Alberto Lavelli
05ca6f4ae400a2e99af6d881295feb059c9f6645
Federated Entity Search using On-The-Fly Consolidation
Federated Entity Search using On-The-Fly Consolidation
Nowadays, search on the Web goes beyond the retrieval of textual Web sites and increasingly takes advantage of the growing amount of structured data. Of particular interest is entity search, where the units of retrieval are structured entities instead of textual documents. These entities reside in different sources, which may provide only limited information about their content and are therefore called “uncooperative”. Further, these sources capture complementary but also redundant information about entities. In this environment of uncooperative data sources, we study the problem of federated entity search, where redundant information about entities is reduced on-the-fly through entity consolidation performed at query time. We propose a novel method for entity consolidation that is based on using language models and completely unsupervised, hence more suitable for this on-the-fly uncooperative setting than state-of-the-art methods that require training data. Further, we apply the same language model technique to deal with the federated search problem of ranking results returned from different sources. Particular novel are the mechanisms we propose to incorporate consolidation results into this ranking. We perform experiments using real Web queries and data sources. Our experiments show that our approach for federated entity search with on-the-fly consolidation improves upon the performance of a state-of-the-art preference aggregation baseline and also benefits from consolidation.
Applications in semantic content management
Isabel Cruz
Isabel Cruz
450162ac52a51c1ed888fa843c004bbc77d8e757
Konstantinos Tarabanis
Konstantinos Tarabanis
Mari Carmen Suárez-Figueroa
Mari Carmen Suárez-Figueroa
TRM – Learning Dependencies between Text and Structure with Topical Relational Models
Sheila Mcilraith
Sheila Mcilraith
One License to Compose Them All: a deontic logic approach to data licensing on the Web of Data
One License to Compose Them All: a deontic logic approach to data licensing on the Web of Data
In the domain of Linked Open Data a need is emerging for developing automated frameworks able to generate the licensing terms associated to data coming from heterogeneous distributed sources. This paper proposes and evaluates a deontic logic semantics which allows us to define the deontic components of the licenses, i.e., permissions, obligations, and prohibitions, and generate a composite license compliant with the licensing items of the composed different licenses. Some heuristics are proposed to support the data publisher in choosing the licenses composition strategy which better suits her needs w.r.t. the data she is publishing.
Instituto Superior Técnico
Instituto Superior Técnico
Italian National Research Council
Italian National Research Council
Wrap-up
Pattern Based Knowledge Base Enrichment
Current research directions in microtask crowdsourcing
Aidan Delaney
Aidan Delaney
Ben Johnston
Ben Johnston
Sarunas Marciuska
Sarunas Marciuska
4e97b2642b9dbf94bee7f0f7a13694c2223b135f
Claudio Giuliano
Claudio Giuliano
8297985c099262b2c5a2704ca281a2b7359a0d96
Cosmin Basca
Cosmin Basca
9a979bd476dd73fdce1663743533e0c9958c2357
Discovering Missing Semantic Relations between Entities in Wikipedia
Sara Winter
Sara Winter
Thorsten Liebig
Thorsten Liebig
University of Economics, Prague
University of Economics, Prague
Tommaso Soru
Tommaso Soru
428d13cbf0747aced7d7969d00f8153326df9644
STI International
STI International
Reliability Analyses of Open Government Data
Reliability Analyses of Open Government Data
Satria Hutomo
Satria Hutomo
fc538c271acda63da4f00543e0f1bf422dc85dc2
Gang Hu
Gang Hu
13fc1184bbdef1b0225adf891fcdbeb1fc27f16a
A GUI for MLN
A GUI for MLN
José Luis Ambite
José Luis Ambite
1e430f2ad8c3dd42da0ac00ed2c6a7c3e6fcaeb5
Stuart Wrigley
Stuart Wrigley
Jie Tang
Jie Tang
Dominique Ritze
Dominique Ritze
Scalable Linked Data Stream Processing via Network-Aware Workload Scheduling
Sarven Capadisli
Sarven Capadisli
Aristotle University of Thessaloniki
Aristotle University of Thessaloniki
Massachusetts Institute of Technology
Massachusetts Institute of Technology
Dan Gillman
Dan Gillman
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/-
Information Integration with Provenance on the Semantic Web via Probabilistic Datalog+/-
Peter Edwards
Peter Edwards
a39911538601368843c38e64f416b47e4be0e936
Besnik Fetahu
Besnik Fetahu
019eb78d2972455d2a0f957cb9f883d357f9ceeb
Michelle Cheatham
Michelle Cheatham
studio labo
studio labo
Incorporating Commercial and Private Data into an Open Linked Data Platform for Drug Discovery
University of Helsinki
University of Helsinki
Shou Matsumoto
Shou Matsumoto
A Distributed Directory System
Leipzig University
Leipzig University
Paris 8 University
Paris 8 University
UMP-ST plug-in: a tool for documenting, maintaing, and evolving probabilistic ontologies
UMP-ST plug-in: a tool for documenting, maintaing, and evolving probabilistic ontologies
Vishwajeet Kumar
Vishwajeet Kumar
a7f3fee56d88bd88187f406139918a1a80e18240
Shepherd Liu
Shepherd Liu
7c795095aa04b60c74c6f14a734cec691c107621
Kevin McAuliffe
Kevin McAuliffe
992b4b6a2a12ac07f8a78690dceb21a6c2e531e4
Secure Manipulation of Linked Data
Gregoire Burel
Gregoire Burel
Canadian Natural Resources
Canadian Natural Resources
Paul Mulholland
Paul Mulholland
2ca9bdb3fb7c2ed6838c50da7847b90c205d1622
Crowdsourcing Linked Data Quality Assessment
Datasets and GATE Evaluation Framework for Benchmarking Wikipedia-Based NER Systems
Efthimios Tambouris
Efthimios Tambouris
Brian Davis
Brian Davis
Andrés Peña
Andrés Peña
Handling uncertainty in semantic information retrieval process
Handling uncertainty in semantic information retrieval process
Registration
INSEE
INSEE
Reasoning on crowd-sourced semantic annotations to facilitate cataloguing of 3D artefacts in the cultural heritage domain
Siu-Ming Tam
Siu-Ming Tam
Discussion: How to standardize benchmarking of NER? Layers, Tasks and Adequacy of Semantic Web technology.
BiographyNet: Managing Provenance at multiple levels and from different perspectives
Edoardo Pignotti
Edoardo Pignotti
Opening Ceremony
Towards Vagueness-Aware Ontologies
Towards Vagueness-Aware Ontologies
Joanneum Research, IIS
Joanneum Research, IIS
Robert Meusel
Robert Meusel
68ff194fb648073f974e8f6fcabf9dc0440db69b
Capturing intent and rationale for Linked Science: design patterns as a resource for linked laboratory experiments
OrdRing 2013 Session 2
Sherif Sakr
Sherif Sakr
ad0629200abede33a02cb519f8d3362c809f7994
Exploiting Semantics from Ontologies and Shared Annotations to Find Patterns in Annotated Linked Open Data
OrdRing 2013 Session 1
TBA
David Lewis
David Lewis
Jim Hendler
Jim Hendler
Jürgen Umbrich
Jürgen Umbrich
54cd3a48f7c3c0d893b06f7de03571968e8d474c
Elena Simperl
Elena Simperl
Lili Jiang
Lili Jiang
Using Linked Data for Web scale IE (II)
Nanchang Hangkong University
Nanchang Hangkong University
A brief introduction to ontology languages & reasoning
Mark Gahegan
Mark Gahegan
Queen Mary, University of London
Queen Mary, University of London
Paris-Sorbonne University
Paris-Sorbonne University
Adrian Mocan
Adrian Mocan
Anastasia Dimou
Anastasia Dimou
f9d7742f673634abec5e8fa870de9b2a0c35be67
Vojtech Svátek
Vojtech Svátek
Pacific Northwest National Laboratory
Pacific Northwest National Laboratory
University of Grenoble
University of Grenoble
Practical Session
Linköping University
Linköping University
Catia Pesquita
Catia Pesquita
f6d8f3f80de6f078840414d8c33b79e96265f2f8
Danila Zaikin
Danila Zaikin
fd6c449834a89d4bc03df255c065b370d781fb18
Japan Advanced Institute of Science and Technology
Japan Advanced Institute of Science and Technology
University of Würzburg
University of Würzburg
Sangyeon Kim
Sangyeon Kim
6b8435482582f87d5450d2e343fcd5ebe80aa460
Jérôme David
Jérôme David
Autonomous University of Madrid
Autonomous University of Madrid
DISQOVER Links For Lives: Building a Linked Data UX (User eXperience) for Federated Query and Faceted Search Linking HealthCare and Life sciences Data for All Users
Cory Henson
Cory Henson
VNU University of Engineering and Technology
VNU University of Engineering and Technology
Noblis
Noblis
Institute for Infocomm Research
Institute for Infocomm Research
Semantic Business Architecture Modelling in Financial Industry Regulation
Rupert Westenthaler
Rupert Westenthaler
Laura Hollink
Laura Hollink
Pontifical Catholic University of Rio de Janeiro
Pontifical Catholic University of Rio de Janeiro
Katherine Wolstencroft
Katherine Wolstencroft
cdb703ede9c7f17070739befd0d3904c4ea85d26
Towards an automatic creation of localized versions of DBpedia
Arne Bröring
Arne Bröring
Daniel Alexander Smith
Daniel Alexander Smith
University of Applied Science Northweastern Switzerland
University of Applied Science Northweastern Switzerland
Rongfang Bie
Rongfang Bie
973b6fbe29329dd193968cfc0fb9ddd64544353a
Vladimir Nevzorov
Vladimir Nevzorov
47e78b7fd826c3e699da83c9fc715a47c678be37
FBK
FBK
TRT - A Tripleset Recommendation Tool
TRT - A Tripleset Recommendation Tool
According to the Linked Data principles, a tripleset should be interlinked with others to take advantage of existing knowledge. However, interlinking is a laborious task. Thus, users interlink their triplesets mostly with data hubs, such as DBpedia and Freebase, ignoring the more specic yet often even more promising triplesets. To alleviate this problem, this paper describes a tripleset interlinking recommendation tool based on link prediction techniques and evaluates the tool on a real-world tripleset repository.
Los Alamos National Laboratory
Los Alamos National Laboratory
Technische Universität Ilmenau
Technische Universität Ilmenau
Cross-language Semantic Retrieval and Linking of E-gov Services
Natasha F. Noy
Natasha F. Noy
7d8b34490f91ef43b84489a7630394b04a8c2c21
Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications
Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications
Cite4Me is a Web application that leverages Semantic Web technologies to provide a new perspective on search and retrieval of bibliographical data. The Web application presented in this work focuses on: (i) semantic recommendation of papers; (ii) novel semantic search & retrieval of papers; (iii) data interlinking of bibliographical data with related data sources from LOD; (iv) innovative user interface design; and (v) sentiment analysis of extracted paper citations. Finally, as this work also targets some educational aspects, our application provides an in-depth analysis of the data that guides a user on his research field.
Geraint A. Wiggins
Geraint A. Wiggins
FZI Forschungszentrum_Informatik
FZI Forschungszentrum_Informatik
Strategic opportunities through applying semantic technologies to modernising official statistics
Ontology-based top-k query answering over massive, heterogeneous, and dynamic data
Ontology-based top-k query answering over massive, heterogeneous, and dynamic data
Assessing the Quality of Semantic Sensor Data
Ghent University
Ghent University
Trina Myers
Trina Myers
Pierre Genevès
Pierre Genevès
NERD: an open source platform for extracting and disambiguating named entities in very diverse documents
Semantic Enrichment of Mobile Phone Data Records Using Linked Open Data
Semantic Enrichment of Mobile Phone Data Records Using Linked Open Data
The pervasivity of mobile phones opens an unprecedented opportunityof deepening into the human dynamics through the analysis of the data they generate.This enables a novel human-driven approach to service creation in a wideset of domains such as health-care, transportation and urban safety. The telecomoperators own and manage billions of mobile network events (like the Call DetailedRecords - CDR) per day: the interpretation of such a big stream of dataneeds a deep understanding of the context where the events have occurred. Theexploitation of available background knowledge is a key element in this scenario.In this paper we introduce a novel method for the semantic interpretation of humanbehavior in mobility based on the merge of the mobile network data streamand the geo-referred available background knowledge. We modeled the humanbehavior making use of the geo and time-referenced knowledge available on theweb (e.g., geo-tagged resources, info on weather forecast, social events, etc.)matching it with the mobile network coverage map. The model is intended tocharacterize the contexts where the mobile network events occur in order to helpin interpreting the behavioral traits that generated by them. This will allow us toachieve a set of predictive tasks such as the prediction of human activities in certain contextual conditions (e.g., when an accident occurs on highway before theworking time starts, etc.), or the characterization of exceptional events detectedfrom anomalies in mobile network data.We created an ontological and stochastic high-level representation behavioralmodel (HRBModel) that maps the human activities to the different contexts.Given the mobile phone network and the geo-tagged resource Openstreetmap,the model is used to rank the activities associated to a particular network event(e.g. a sudden call amount peak) according to their probability. We also describethe design of an experimental evaluation and the preliminary evaluation resultsto measure the performance of the model and to improve the activity predictiontask.
Australian Bureau of Statistics Implementation of Semantic Web Technology
Australian National University
Australian National University
Peter Christen
Peter Christen
0ba1ef9c483a13f58163078239e74cecb6ea1e4a
Ontology Evolution for End-User Communities
Ontology Evolution for End-User Communities
Carolina Fortuna
Carolina Fortuna
From Strings to Things SAR-Graphs: A New Type of Resource for Connecting Knowledge and Language
SemantEco Annotator
SemantEco Annotator
Generating useful RDF linked data is not a straightforward process for scientists using today’s tools. In this paper we introduce the SemantEco Annotator, a semantic web application that leverages community-based vocabularies and ontologies during the translation process itself to ease the process of drawing out implicit relationships in tabular data so that they may be immediately available for use within the LOD cloud. Our goal for the SemantEco Annotator is to make advanced RDF translation techniques available to the layperson.
Apoorva Rao Balevalachilu
Apoorva Rao Balevalachilu
255fa9053ca6ab1b23c6a4ffdd1a94dc1bd85325
Gianluca Demartini
Gianluca Demartini
4d89f6919da4047bbcaad20bad01e1dd62b4578f
Pierre Chaussecourte
Pierre Chaussecourte
492ba135659c8f275248f4cf3729c56fdd32aaaf
Jönköping University
Jönköping University
Goldsmiths, University of London
Goldsmiths, University of London
Peter Wetz
Peter Wetz
An explicit OWL representation of ISO/OGC Observations and Measurements
Amazon’s Mechanical Turk hands-on
Television meets the Web: a Multimedia Hypervideo Experience
Television meets the Web: a Multimedia Hypervideo Experience
To repair or not to repair: reconciling correctness and coherence in ontology reference alignments
Jay Pujara
Jay Pujara
d3b8f92ab3c0f6e28f70810c61c963cedb86d9fb
The Web of Things Session 1
Mihaela Bornea
Mihaela Bornea
Yevgeny Kazakov
Yevgeny Kazakov
281ba0a9b09b378e1928e73e75d97c58782096a9
University of Maryland, College Park
University of Maryland, College Park
Steve Pettifer
Steve Pettifer
Claudio Gutierrez
Claudio Gutierrez
f341588c8c974d3b6fa4134e12700da871e8704f
Aidan Hogan
Aidan Hogan
d2163e057507f828085f322cc77dc43b4105a158
Christian Chiarcos
Christian Chiarcos
Ricoh Europe plc
Ricoh Europe plc
Event dashboard: Capturing user-defined semantics events for event detection over real-time sensor data
Werner Kuhn
Werner Kuhn
Unsupervised learning of link specifications: deterministic vs. non-deterministic
NLP for Interlinking Multilingual LOD
NLP for Interlinking Multilingual LOD
Claire D'Este
Claire D'Este
University of Oviedo
University of Oviedo
Welcome
University of Mannheim
University of Mannheim
Enrico Franconi
Enrico Franconi
cc31df1716defe7e7094b4e019d2218078072e53
Daniel M. Herzig
Daniel M. Herzig
4ee687e8f9e8576a48ec7625e7ccc414fcd57639
Gully Burns
Gully Burns
Semantic Interpretation of Mobile Phone Records Exploiting Background Knowledge
Semantic Interpretation of Mobile Phone Records Exploiting Background Knowledge
Johannes Hoffart
Johannes Hoffart
bb43cd4c4209a7e7c368ba917ec884f8947ae595
Elizabeth Cano
Elizabeth Cano
Ming Mao
Ming Mao
Hands-on Guide to Linked Data Applications Session 2
Short Introduction to the Workshop
Adaptive Navigation through Semantic Annotations and Service Descriptions
Adaptive Navigation through Semantic Annotations and Service Descriptions
The Web of Things Session 2
Laurent Lefort
Laurent Lefort
32e377e401d35473ce349f7f0970cdb7b2dacdee
Barry Norton
Barry Norton
6a5237d33f908291f9d94014f12fe4bb7a3e58f1
Intersticia
Intersticia
Carlos Buil Aranda
Carlos Buil Aranda
250a676d59d5e43d3d41c99fa31c016132e9ee0f
Mitre Corporation
Mitre Corporation
Hands-on Guide to Linked Data Applications Session 1
Mark Wilkinson
Mark Wilkinson
Alexander Schätzle
Alexander Schätzle
406429b970021d69db594b17e3dcde173259fa79
Fariz Darari
Fariz Darari
8a9303d7ee01a54736bcc17c37f533d85d6ae6f4
Franky
Franky
Hewlett Packard Laboratories
Hewlett Packard Laboratories
Martin Giese
Martin Giese
9cc447f0f4877bc04e7d6703bf040d7337094e65
CrowdSem: Crowdsourcing the Semantic Web
Giuseppe Pirrò
Giuseppe Pirrò
711256fae69b7261d5b1b342a77179b2df810f03
Alexander Kirillovich
Alexander Kirillovich
6a27a24da98e769d1f193575c9b78169c7c4c23c
Livia Predoiu
Livia Predoiu
Neofonie
Neofonie
Roi Blanco
Roi Blanco
adf69612f64a39dc0fb242f882df9958bf7b45ad
Karthik Rajendra Prasad
Karthik Rajendra Prasad
b956df377789855d08d1cb5ca812b59bc340893a
Using Linked Data to evaluate the impact of Research and Development in Europe: a Structural Equation Model
Using Linked Data to evaluate the impact of Research and Development in Europe: a Structural Equation Model
Europe has a high impact on the global biomedical literature, having contributed with a growing number of research articles and a significant citation impact. However, the impact of research and development generated by European countries on economic, educational and healthcare performance is poorly understood. The recent Linking Open Data (LOD) project has made a lot of data sources publicly available and in human-readable formats. In this paper, we demonstrate the utility of LOD in assessing the impact of Research and Development (R&D) on the economic, education and healthcare performance in Europe. We extract relevant variables from two LOD datasets, namely World Bank and Eurostat. We analyze the data for 20 out of the 27 European countries over a span of 10 years (1999 to 2009). We use a Structural Equation Modeling (SEM) approach to quantify the impact of R&D on the different measures. We perform different exploratory and confirmatory factorial analysis evaluations which gives rise to four latent variables that are included in the model: (i) Research and Development (R&D), (ii) Economic Performance (EcoP), (iii) Educational Performance (EduP), (iv) Healthcare performance (HcareP) of the European countries. Our results indicate the importance of R&D to the overall development of the European educational and healthcare performance (directly) and economic performance (indirectly). The results also shows the practical applicability of LOD to estimate this impact.
Crowdsourcing Linked Data Quality Assessment
Crowdsourcing Linked Data Quality Assessment
In this paper we look into the use of crowdsourcing as a means to handle Linked Data quality problems that are challenging to be solved automatically. We analyzed the most common errors encountered in Linked Data sources and classified them according to the extent to which they are likely to be amenable to a specific form of crowdsourcing. Based on this analysis, we implemented a quality assessment methodology for Linked Data that leverages the wisdom of the crowds in different ways: (i) a contest targeting an expert crowd of researchers and Linked Data enthusiasts; complemented by (ii) paid microtasks published on Amazon Mechanical Turk. We empirically evaluated how this methodology could efficiently spot quality issues in DBpedia. We also investigated how the contributions of the two types of crowds could be optimally integrated into Linked Data curation processes. The results show that the two styles of crowdsourcing are complementary and that crowdsourcing-enabled quality assessment is a promising and affordable way to enhance the quality of Linked Data.
Which of the following SPARQL Queries are Similar? Why?
Rinke Hoekstra
Rinke Hoekstra
Braunschweig University of Technology
Braunschweig University of Technology
University of Turin
University of Turin
Martin Brümmer
Martin Brümmer
1e703d9aa0e8bc8eda4e46d183e8af25fe03ab44
Milan Markovic
Milan Markovic
02ed7152b175942f80b8526d1f647440851e4487
Sebastian Rudolph
Sebastian Rudolph
CrowdSem Session 2
University of Illinois at Chicago
University of Illinois at Chicago
Charalampos Bratsas
Charalampos Bratsas
Semantic Data and Models Sharing in systems Biology: The Just Enough Results Model and the SEEK Platform
Semantic Data and Models Sharing in systems Biology: The Just Enough Results Model and the SEEK Platform
Research in Systems Biology involves integrating data and knowledge about the dynamic processes in biological systems in order to understand and model them. Semantic web technologies should be ideal for exploring the complex networks of genes, proteins and metabolites that interact, but much of this data is not natively available to the semantic web. Data is typically collected and stored with free-text annotations in spreadsheets, many of which do not conform to existing metadata standards and are often not publica lly released. Along with initiatives to promote more data sharing, one of the main challenges is therefore to semantically annotate and extract this data so that it is available to the research community. Data annotation and curation are expensive and undervalued tasks that have enormous benefits to the discipline as a whole, but fewer benefits to the individual data producers. By embedding semantic annotation into spreadsheets, however, and automat ically extracting this data into RDF at the time of repository submission, the process of producing standards-compliant data, that is available for semantic web querying, can be achieved without adding additional overheads to laboratory data management. This paper describes these strategies in the context of semantic data management in the SEEK. The SEEK is a web-based resource for sharing and exchanging Systems Biology data and models that is underpinned by the JERM ontology (Just Enough Results Model), which describes the relationships between data, models, protocols and experiments. The SEEK was originally developed for SysMO, a large European Systems Biology consortium studying micro-organisms, but it has since had widespread adoption across European Systems Biology.
Hong-Gee Kim
Hong-Gee Kim
Axel Polleres
Axel Polleres
FTW Telecommunications Research Center Vienna
FTW Telecommunications Research Center Vienna
Bassem Makni
Bassem Makni
Ansgar Scherp
Ansgar Scherp
b9dd60bd56a27cdc0554f7461ee6ca0ed6346385
CrowdSem Session 1
Charles Vardeman
Charles Vardeman
Lexing Xie
Lexing Xie
cdaea6d4dff62443bcc7337dc2e4226bd6eaa398
Lehigh University
Lehigh University
Emanuel Santos
Emanuel Santos
c29bfb65d09982d5ed97832ea9682cb3ddf318f0
CELCT
CELCT
Magnus Knuth
Magnus Knuth
Mohsen Taheriyan
Mohsen Taheriyan
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Muhammad Saleem
Muhammad Saleem
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Reasoning on crowd-sourced semantic annotations to facilitate cataloguing of 3D artefacts in the cultural heritage domain
Reasoning on crowd-sourced semantic annotations to facilitate cataloguing of 3D artefacts in the cultural heritage domain
The 3D Semantic Annotation (3DSA) system expedites the classification of 3D digital surrogates from the cultural heritage domain, by leveraging crowd-sourced semantic annotations. More specifically, the 3DSA system generates high-level classifications of 3D ob jects by applying rule-based reasoning across community-generated annotations and low-level shape and size attributes. This paper describes a particular use of the 3DSA system – cataloguing Greek pottery. It also describes our novel approach to rule-based reasoning that is modelled on concepts inspired from Markov logic networks. Our evaluation of this approach demonstrates its efficiency, accuracy and versatility, compared to classical rule-based reasoning.
Kamel Nebhi
Kamel Nebhi
Masatomo Goto
Masatomo Goto
David L. Buckeridge
David L. Buckeridge
db20b90c3b41f05f1b030e7fdf5b307fe9c8d4b4
Integrating NLP using Linked Data
Change-a-LOD: Does the Schema on the Linked Data Cloud Change or Not?
Change-a-LOD: Does the Schema on the Linked Data Cloud Change or Not?
Full Syntactic Parsing for Enrichment of RDF dataset
Graham Klyne
Graham Klyne
Welcome and workshop overview
Real-time Urban Monitoring in Dublin using Semantic and Stream Technologies
Real-time Urban Monitoring in Dublin using Semantic and Stream Technologies
Several sources of information, from people, systems, things, are already available in most modern cities. Processing these continuous flows of information and capturing insight poses unique technical challenges that span from response time constraints to data heterogeneity, in terms of format and throughput. To tackle these problems, we focus on a novel prototype to ease real-time monitoring and decision-making processes for the City of Dublin with three main original technical aspects: (i) an extension to SPARQL to support efficient querying of heterogeneous streams; (ii) a query execution framework and runtime environment based on IBM InfoSphere Streams, a high-performance, industrial strength, stream processing engine; (iii) a hybrid RDFS reasoner, optimized for our stream processing execution framework. Our approach has been validated with real data collected on the field, as shown in our Dublin City video demonstration. Results indicate that real-time processing of city information streams based on semantic technologies is indeed not only possible, but also efficient, scalable and low-latency.
SemStats 2013 Session 1
Jemma Wu
Jemma Wu
6437625d426cc5957ed095d5a864869fcbf3ca75
Anya Okhmatovskaia
Anya Okhmatovskaia
b7ec865d98f49502b1270476ba496e056ba6811e
Consuming Linked data in Supply Chains: Enabling data visibility via Linked Pedigrees
Consuming Linked data in Supply Chains: Enabling data visibility via Linked Pedigrees
Semantic Rule Filtering for Web-Scale Relation Extraction
Johanna Völker
Johanna Völker
2e00f888d43b46c52a387ae4027c88a69be4eae7
Linked Data for Cross-disciplinary Collaboration Cohort Discovery
Rapid execution of weighted edit distances
Pedro Szekely
Pedro Szekely
89ff2466008411464749069a197222abbfec05f3
Using Semantic Web in ICD-11: Three Years Down the Road
Using Semantic Web in ICD-11: Three Years Down the Road
The World Health Organization is using Semantic Web technologies in the development of the 11th revision of the International Classification of Diseases (ICD-11). Health officials use ICD in all United Nations member countries to compile basic health statistics, to monitor health-related spending, and to inform policy makers. In 2010, we published a paper in the ISWC In Use track reporting on our experience in the first six months with building and deploying iCAT, a Semantic Web platform to support the collaborative authoring of ICD-11. Three years since our original publication, 270 domain experts around the world have used iCAT to author more than 45,000 classes, to perform more than 260,000 changes, and to create more than 17,000 links to external medical terminologies. During the last three years, the collaboration processes, modeling and tooling have evolved significantly, and we have learned important lessons, which we will report in this paper. We describe the benefits of using semantic technologies as an infrastructure, which proved to be critical in making support for this rapid evolution possible. To our knowledge, this effort is the only real-world pro ject supporting the collaborative authoring of ontologies at this scale, and which, at the same time, has a high visibility and impact for the health care around the world. We believe that the insights that we gained and the lessons that we learned after four years into this large-scale pro ject will be useful to others who need to support similar collaborative pro jects.
SemStats 2013 Session 2
Philipp Cimiano
Philipp Cimiano
Stratos Idreos
Stratos Idreos
Diego Reforgiato Recupero
Diego Reforgiato Recupero
Bringing Math to LOD: A Semantic Publishing Platform Prototype for Scientific Collections in Mathematics
Nicola Fanizzi
Nicola Fanizzi
SemStats 2013 Session 4
Philip Stutz
Philip Stutz
4a882a6281cdbc0fd61cd836e251a6334035d2dc
Claudia D'Amato
Claudia D'Amato
Triplifying Wikipedia's Tables
University of Zurich
University of Zurich
Evgeny Kharlamov
Evgeny Kharlamov
dc1d47b43c3d22ef49202d417a7cf655057bcfd7
Named Entity Disambiguation using Freebase and Syntactic Parsing
Complete Query Answering Over Horn Ontologies Using a Triple Store
Complete Query Answering Over Horn Ontologies Using a Triple Store
In our previous work, we showed how a scalable OWL 2 RL reasoner can be used to compute both lower and upper bound query answers over very large datasets and arbitrary OWL 2 ontologies. However, when these bounds do not coincide, there still remain a number of possible answer tuples whose status is not determined. In this paper, we show how in the case of Horn ontologies one can exploit the lower and upper bounds computed by the RL reasoner to efficiently identify a subset of the data and ontology that is large enough to resolve the status of these tuples, yet small enough so that the status can be computed using a fully-fledged OWL 2 reasoner. The resulting hybrid approach has enabled us to compute exact answers to queries over datasets and ontologies where previously only approximate query answering was possible.
Using the past to explain the present: interlinking current affairs with archives via the Semantic Web
Using the past to explain the present: interlinking current affairs with archives via the Semantic Web
The BBC has a very large archive of programmes, covering a wide range of topics. This archive holds a significant part of the BBC’s institutional memory and is an important part of the cultural history of the United Kingdom and the rest of the world. These programmes, or parts of them, can help provide valuable context and background for current news events. However the BBC’s archive catalogue is not a complete record of everything that was ever broadcast. For example, it excludes the BBC World Service, which has been broadcasting since 1932. This makes the discovery of content within these parts of the archive very difficult. In this paper we describe a system based on Semantic Web technologies which helps us to quickly locate content related to current news events within those parts of the BBC’s archive with little or no pre-existing metadata. This system is driven by automated interlinking of archive content with the Semantic Web, user validations of the resulting data and topic extraction from live BBC News subtitles. The resulting inter-links between live news subtitles and the BBC’s archive are used in a dynamic visualisation enabling users to quickly locate relevant content. This content can then be used by journalists and editors to provide historical context, background information and supporting content around current affairs.
Institut Eurécom
Institut Eurécom
Jeff Heflin
Jeff Heflin
1d8b1638f1c01384c2d034bb1853ecbe8952a4aa
Carl-Martin Marquardt
Carl-Martin Marquardt
Bogdan Kostov
Bogdan Kostov
SemStats 2013 Session 3
DBpedia & NLP 2013
Anton Feenstra
Anton Feenstra
Tim Crawford
Tim Crawford
Mingyang Li
Mingyang Li
Self-Sustaining Platforms: a Semantic Workflow Engine
Self-Sustaining Platforms: a Semantic Workflow Engine
Khadija Elbedweihy
Khadija Elbedweihy
Ludger van Elst
Ludger van Elst
LD4IE Wrap-up and open discussion
Guo Tong Xie
Guo Tong Xie
f5c34dd1538d2a82798ba9b1ff312b6f477149c1
Publishing the Norwegian Petroleum Directorate’s FactPages as Semantic Web Data
Publishing the Norwegian Petroleum Directorate’s FactPages as Semantic Web Data
This paper motivates, documents and evaluates the process and results of converting the Norwegian Petroleum Directorate’s Fact-Pages, a well-known and diverse set of tabular data, but with little and incomplete schema information, stepwise into other representations where in each step more semantics is added to the dataset. The different representations we consider are a regular relational database, a linked open data dataset, and an ontology. For each conversion step we explain and discuss necessary design choices which are due to the specific shape of the dataset, but also those due to the characteristics and idiosyncrasies of the representation formats. We additionally evaluate the output, performance and cost of querying the different formats using questions provided by users of the FactPages.
Asunción Gómez-Pérez
Asunción Gómez-Pérez
Statistical Knowledge Patterns: Identifying Synonymous Relations in Large Linked Datasets
Statistical Knowledge Patterns: Identifying Synonymous Relations in Large Linked Datasets
The Web of Data is a rich common resource with billions of triples available in thousands of datasets and individual Web documents created by both expert and non-expert ontologists. A common problem is the imprecision in the use of vocabularies: annotators can misunderstand the semantics of a class or property or may not be able to find the right objects to annotate with. This decreases the quality of data and may eventually hamper its usability over large scale. This paper describes Statistical Knowledge Patterns (SKP) as a means to address this issue. SKPs encapsulate key information about ontology classes, including synonymous properties in (and across) datasets, and are automatically generated based on statistical data analysis. SKPs can be effectively used to automatically normalise data, and hence increase recall in querying. Both pattern extraction and pattern usage are completely automated. The main benefits of SKPs are that: (1) their structure allows for both accurate query expansion and restriction; (2) they are context dependent, hence they describe the usage and meaning of properties in the context of a particular class; and (3) they can be generated offline, hence the equivalence among relations can be used efficiently at run time.
Volker Haarslev
Volker Haarslev
Zhigang Wang
Zhigang Wang
16c2aee7bca63a67923b529a4287eb7f0751c928
Swiss Institute of Bioinformatics
Swiss Institute of Bioinformatics
Fausto Giunchiglia
Fausto Giunchiglia
Marco Miglierina
Marco Miglierina
Keerthi Thomas
Keerthi Thomas
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Siaw-Teng Liaw
Siaw-Teng Liaw
bbc95a8ebc4608658006361d136ab2b8b3386d32
Giuseppe Rizzo
Giuseppe Rizzo
A Semantic Approach to Data Center Management
Sofia Angeletou
Sofia Angeletou
Volha Bryl
Volha Bryl
Bridgewater College
Bridgewater College
Marieke Van Erp
Marieke Van Erp
44f447544cd755d83c1e50e4e92c09d015c240eb
Domingo De Abreu
Domingo De Abreu
4de4b15777bf0685922ded769728ee353403560e
Uli Sattler
Uli Sattler
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Christin Seifert
Christin Seifert
a9297d629b5d7c10a573e679a76e40fb32d18d47
Cosmin Stroe
Cosmin Stroe
84b14429c32c94ff7dd30968c01e6be9614bf915
Juan Carlos Corrales
Juan Carlos Corrales
University of Fribourg
University of Fribourg
How Semantic Technologies supercharge a platform for context-aware applications
Francesco Osborne
Francesco Osborne
651c4a4af5ab4db99ecc207b495be0cc351e86e8
Baoshi Yan
Baoshi Yan
Francois Scharffe
Francois Scharffe
Anni Rowland-Campbell
Anni Rowland-Campbell
Royal Dutch Academy of Sciences
Royal Dutch Academy of Sciences
IAA-CSIC
IAA-CSIC
Grant McKenzie
Grant McKenzie
4c279b3b17743127a846a3317398ebc552c0535b
Eva Blomqvist
Eva Blomqvist
6ae81c4db26362dadb297719b4178e23dd011c6d
A Linked-Data-driven and Semantically-enabled Journal Portal for Scientometrics
A Linked-Data-driven and Semantically-enabled Journal Portal for Scientometrics
The Semantic Web journal by IOS Press follows a unique open and transparent process during which each submitted manuscript is available online together with the full history of its successive decision statuses, assigned editors, solicited and voluntary reviewers, their full text reviews, and in many cases also the authors’ response letters. Combined with a highly-customized, Drupal-based journal management system, this provides the journal with semantically rich manuscript time lines and networked data about authors, reviewers, and editors. These data are now exposed using a SPARQL endpoint, an extended Bibo ontology, and a modular Linked Data portal that provides interactive scientometrics based on established and new analysis methods. The portal can be customized for other journals as well.
Semantic Machine Learning and Linked Open Data Application
Carsten Binnig
Carsten Binnig
71da1f44273f7872928298e947547ba68321f1c6
Yongtao Ma
Yongtao Ma
f062893fcb05d2e45eae8d04a8e322a622bcc4bf
RSC
RSC
Towards an RDF Analytics Language: Learning from Successful Experiences
Towards an RDF Analytics Language: Learning from Successful Experiences
Invited Talk -- Andrew Woolf
Emilie Hogan
Emilie Hogan
Cross-language Semantic Retrieval and Linking of E-gov Services
Cross-language Semantic Retrieval and Linking of E-gov Services
Public administrations are aware of the advantages of sharing Open Government Data in terms of transparency, development of improved services, collaboration between stakeholders, and spurring new economic activities. Initiatives for the publication and interlinking of government service catalogs as Linked Open Data (lod) support the interoperability among European administrations and improve the capability of foreign citizens to access services across Europe. However, linking service catalogs to reference lod catalogs requires a significant effort from local administrations, preventing the uptake of interoperable solutions at a large scale. The web application presented in this paper is named CroSeR (Cross-language Service Retriever) and supports public bodies in the process of linking their own service catalogs to the lod cloud. CroSeR supports different European languages and adopts a semantic representation of e-gov services based on Wikipedia. CroSeR tries to overcome problems related to the short textual descriptions associated to a service by embodying a semantic annotation algorithm that enriches service labels with emerging Wikipedia concepts related to the service. An experimental evaluation carried-out on e-gov service catalogs in five different languages shows the effectiveness of our model.
Simona Valentini
Simona Valentini
e614b9813fc8a4eb97a1101c8a3869847baad40d
1st International Workshop on Semantic Statistics
Medha Atre
Medha Atre
Hong Li
Hong Li
61c3d3c9b7ba65cde83664cdd2a30477bb96a8f7
Peter Mika
Peter Mika
c0d6551197a0295bfc604841a994d544e0091665
LD4IE Session 1
Linked Data for Financial Reporting
Linked Data for Financial Reporting
Andrew McParland
Andrew McParland
42196cba177fd0feb4722bce2f900f51cb107b74
When History Matters - Assessing Reliability for the Reuse of Scientific Workflows
When History Matters - Assessing Reliability for the Reuse of Scientific Workflows
Scientific workflows play an important role in computational research as essential artifacts for communicating the methods used to produce research findings. We are witnessing a growing number of efforts that treat workflows as first-class artifacts for sharing and exchanging scientific knowledge, either as part of scholarly articles or as standalone ob jects. However, workflows are not born to be reliable, which can seriously damage their reusability and trustworthiness as knowledge exchange instruments. Scientific workflows are commonly sub ject to decay, which consequently undermines their reliability over their lifetime. The reliability of workflows can be notably improved by advocating scientists to preserve a minimal set of information that is essential to assist the interpretations of these workflows and hence improve their potential for reproducibility and reusability. In this paper we show how, by measuring and monitoring the completeness and stability of scientific workflows over time we are able to provide scientists with a measure of their reliability, supporting the reuse of trustworthy scientific knowledge.
Trish Whetzel
Trish Whetzel
3111e1cc48329edb3c57f4f0204bca5dd4f69e0b
University of Crete
University of Crete
LD4ID session 2
Rights declaration in Linked Data
Rights declaration in Linked Data
Ahmed Abdelrahman
Ahmed Abdelrahman
d831360cc8f8ba4ef5f1915378c36088fd5dd390
McGill University
McGill University
Integrating NLP using Linked Data
Integrating NLP using Linked Data
We are currently observing a plethora of Natural Language Processing tools and services being made available. Each of the tools and services has its particular strengths and weaknesses, but exploiting the strengths and synergistically combining different tools is currently an extremely cumbersome and time consuming task. Also, once a particular set of tools is integrated, this integration is not reusable by others. We argue that simplifying the interoperability of different NLP tools performing similar but also complementary tasks will facilitate the comparability of results and the creation of sophisticated NLP applications. In this paper, we present the NLP Interchange Format (NIF). NIF is based on a Linked Data enabled URI scheme for identifying elements in (hyper-)texts and an ontology for describing common NLP terms and concepts. In contrast to more centralized solutions such as UIMA and GATE, NIF enables the creation of heterogeneous, distributed and loosely coupled NLP applications, which use the Web as an integration platform. We present several use cases of the second version of the NIF specification (NIF 2.0) and the result of a developer study.
Francesco Draicchio
Francesco Draicchio
2c3fdeff798137aac620534b6c1e1ecaf3ca824a
Marco Combetto
Marco Combetto
The 12th International Semantic Web Conference
LD4IE Session 3
BBN Technologies
BBN Technologies
Li Ding
Li Ding
Linked Data Platform as a novel approach for Enterprise Application Integration
Linked Data Platform as a novel approach for Enterprise Application Integration
TNO, Netherlands
TNO, Netherlands
Karlsruhe Institute of Technology
Karlsruhe Institute of Technology
Pascal Gillet
Pascal Gillet
Elena Peterson
Elena Peterson
ProSWIP: Property-based Data Access for Semantic Web Interactive Programming
Do it yourself (DIY) Jeopardy QA System
Do it yourself (DIY) Jeopardy QA System
This work demonstrates Treo, a framework which converges elements from Natural Language Processing, Semantic Web, Information Retrieval and Databases, to create a semantic search engine and question answering (QA) system for heterogeneous data. Jeopardy and Question Answering queries over open domain structured and unstructured data are used to demonstrate the approach. In this work, Treo is extended to cope with unstructured data in addition to structured data. The setup of the framework is done in 3 steps and can be adapted to other datasets by practitioners in a simple DIY process.
Yolanda Gil
Yolanda Gil
Assessing the Quality of Semantic Sensor Data
Assessing the Quality of Semantic Sensor Data
FedSearch: efficiently combining structured queries and full-text search in a SPARQL federation
Vadim Ivanov
Vadim Ivanov
2b051c345476ebf92e3b7f0ec3a959e8c2614a37
Gianluca Correndo
Gianluca Correndo
Knowledge Graph Identification
A Machine Reader for the Semantic Web
A Machine Reader for the Semantic Web
FRED is a machine reading tool for converting text into internally well-connected and quality linked-data-ready ontologies in web-service-acceptable time. It implements a novel approach for ontology design from natural language sentences, combining Discourse Representation Theory (DRT), linguistic frame semantics, and Ontology Design Patterns (ODP). The tool is based on Boxer which implements a DRT-compliant deep parser. The logical output of Boxer is enriched with semantic data from VerbNet (or FrameNet) frames and transformed into RDF/OWL by means of a mapping model and a set of heuristics following best practices of OWL ontologies and RDF data design. The current version of the tool includes Earmark-based markup, and enrichment with WSD and NER off-the-shelf components.
Sven Schewe
Sven Schewe
2a831f2810dc93308e523fa0bdf45a2779b6d0a6
Marat Charlaganov
Marat Charlaganov
60374cc25405f74b986d94b2a003764f65bbcd72
Manuel Salvadores
Manuel Salvadores
Thomas Grotton
Thomas Grotton
OData and the Semantic Web
OData and the Semantic Web
From RESTful to SPARQL: A Case Study on Generating Semantic Sensor Data
From RESTful to SPARQL: A Case Study on Generating Semantic Sensor Data
SPARQL Web-Querying Infrastructure: Ready for Action?
TopQuadrant Inc.
TopQuadrant Inc.
Karl Hammar
Karl Hammar
Alberto Tonon
Alberto Tonon
3b41efd1acf36406793166b43659b542c431776f
An explicit OWL representation of ISO/OGC Observations and Measurements
An explicit OWL representation of ISO/OGC Observations and Measurements
Type Inference on Noisy RDF Data
SEJP: Designing Interactive Scientometrics with Linked Data and Semantic Web Reasoning
SEJP: Designing Interactive Scientometrics with Linked Data and Semantic Web Reasoning
In this demo paper we introduce a Linked Data-driven, Semantically-enabled Journal Portal (SEJP) that offers a variety of interactive scientometrics modules. SEJP allows editors, reviewers, authors, and readers to explore and analyze (meta)data published by a journal. Besides Linked Data created from the journal's internal data, SEJP also links out to other sources and includes them to develop more powerful modules. These modules range from simple descriptive statistics, over the spatial analysis of visitors and authors, to topics trending modules. While SEJP will be available for multiple journals, this paper shows its deployment to the Semantic Web journal by IOS Press. Due to its open & transparent review process, SWJ offers a wide variety of additional information, e.g., about reviewers, editors, paper decisions, and so forth.
Nadeschda Nikitina
Nadeschda Nikitina
6acf6508684c36b1ae83b2765bc22260799454e2
Ernesto Jiménez-Ruiz
Ernesto Jiménez-Ruiz
8542cc0914fc0bf5758ae966df4abed2dd011172
Content-Preserving Graphics
Content-Preserving Graphics
NoSQL Databases for RDF: An Empirical Evaluation
Jacky. L. Snoep
Jacky. L. Snoep
Maastricht University
Maastricht University
Steve Benford
Steve Benford
Big Data Management Session 1
ONTOMS2: an Efficient and Scalable ONTOlogy Management System with an Incremental Reasoning
ONTOMS2: an Efficient and Scalable ONTOlogy Management System with an Incremental Reasoning
We present ONTOMS2, an efficient and scalable ONTOlogy Management System with an incremental reasoning. ONTOMS2 stores an OWL document and processes OWL-QL and SPARQL queries. Especially, ONTOMS2 supports SPARQL Update queries with an incremental instance reasoning of inverseOf, symmetric and transitive properties.
Statistical Knowledge Patterns: Identifying Synonymous Relations in Large Linked Datasets
Wen Wen
Wen Wen
Renata Dividino
Renata Dividino
a40b3aefc5904bb37d3a1d81fc1ee8d8d16e3348
Dmitry Tsarkov
Dmitry Tsarkov
8ca9de5243d9babda9bdbc832bfabdd8e6aaed36
Event dashboard: Capturing user-defined semantics events for event detection over real-time sensor data
Event dashboard: Capturing user-defined semantics events for event detection over real-time sensor data
Kai-Uwe Sattler
Kai-Uwe Sattler
M. Mustafa Rafique
M. Mustafa Rafique
872b93c8f5394de8ef3b1f1faa1b9b747c39662c
Fondazione Bruno Kessler
Fondazione Bruno Kessler
Hairong Yu
Hairong Yu
79bb0532c9c1428e6c5c74bc9ea44ed208b52ee9
Big Data Management Session 2
Domain-Independent Quality Measures for Crowd Truth Disagreement
KONA LLC
KONA LLC
SPACE: SParql index for efficient Auto ComplEtion
SPACE: SParql index for efficient Auto ComplEtion
Querying Linked Data means to pose queries on various data sources without information about the data and the schema of the data. This demo shows SPACE, a tool to support autocompletion for SPARQL queries. It takes as input SPARQL query logs and builds an index structure for efficient and fast computation of query suggestions. To demonstrate SPACE, we use available query logs from the USEWOD Data Challenge 2013.
Jens Lehmann
Jens Lehmann
01fee219e665ecea3905f361517b2bd4a344975d
Knowledge Discovery
Aparna Nagarajan
Aparna Nagarajan
908524fc2fa3c0794cc44df8659ee0b023321f89
DISQOVER Links For Lives: Building a Linked Data UX (User eXperience) for Federated Query and Faceted Search Linking HealthCare and Life sciences Data for All Users
DISQOVER Links For Lives: Building a Linked Data UX (User eXperience) for Federated Query and Faceted Search Linking HealthCare and Life sciences Data for All Users
tablet-based visualisation of transport data in Madrid using SPARQL-Stream
tablet-based visualisation of transport data in Madrid using SPARQL-Stream
Bin He
Bin He
Themis Palpanas
Themis Palpanas
f7683805b420974c935918af66c6f3e8dbe1c009
Valentina Tamma
Valentina Tamma
Listening to the pulse of our cities during City Scale Events
Query
Denilson Barbosa
Denilson Barbosa
How Semantic Technologies supercharge a platform for context-aware applications
How Semantic Technologies supercharge a platform for context-aware applications
GSK
GSK
Patrick Lambrix
Patrick Lambrix
SexTant: Visualizing Time-Evolving Linked Geospatial Data
SexTant: Visualizing Time-Evolving Linked Geospatial Data
The linked open data cloud is constantly evolving as datasets are continuously updated with newer versions. As a result, representing, querying, and visualizing the temporal dimension of linked data is crucial. This is especially important for geospatial datasets that form the backbone of large scale open data publication efforts in many sectors of the economy (the public sector, the Earth observation sector). Although there has been some work on the representation and querying of linked geospatial data that change over time, to the best of our knowledge, there is currently no tool that offers spatio-temporal visualization of such data. In this demo paper we present the system SexTant that addresses this issue. SexTant is a web-based tool that enables the exploration of time-evolving linked geospatial data as well as the creation, sharing, and collaborative editing of "temporally-enriched" thematic maps by combining different sources of geospatial and temporal information.
University of Kassel
University of Kassel
Petr Křemen
Petr Křemen
Chinese Academy of Sciences
Chinese Academy of Sciences
LIG
LIG
CWI Amsterdam
CWI Amsterdam
Ontology Mapping
Mark Sandler
Mark Sandler
The Combined Approach to OBDA: Taming Role Hierarchies using Filters
Carlos Pedrinaci
Carlos Pedrinaci
An Ontology Framework for Water Quality Management
An Ontology Framework for Water Quality Management
Integrating Relational Databases with the Semantic Web: Four Scenarios
Integrating Relational Databases with the Semantic Web: Four Scenarios
The Empirical Robustness of Description Logic Classification
The Empirical Robustness of Description Logic Classification
In spite of the recent renaissance in lightweight description logics (DLs), many prominent DLs, such as that underlying the Web Ontology Language (OWL), have high worst case complexity for their key inference services. Modern reasoners have a large array of optimization, tuned calculi, and implementation tricks that allow them to perform very well in a variety of application scenarios, even though the complexity results ensure that they will perform poorly for some inputs. For users, the key question is how often they will encounter those pathological inputs in practice, that is, how robust are reasoners. We attempt to determine this question for classification of existing ontologies as they are found on the Web. It is a fairly common user task to examine ontologies published on the Web as part of their development process. Thus, the robustness of reasoners in this scenario is both directly interesting and provides some hints toward answering the broader question. From our experiments, we show that the current crop of OWL reasoners, in collaboration, is very robust against the Web.
Seme4
Seme4
Jean-Paul Calbimonte
Jean-Paul Calbimonte
b33a4918bf12bc9dd4115ed53ade46736ec3b7db
Piero Bonatti
Piero Bonatti
c3e584412f354d544dcfa72b4407bbc082b11063
FRED as an Event Extraction Tool
Ontology-Based Data Access: Ontop of Databases
Antske Fokkens
Antske Fokkens
211e24eb99a42047ee5ca8d05890ba2fcc6ca8b8
Citizen Sensing within a Real Time Passenger Information System
Citizen Sensing within a Real Time Passenger Information System
Juan Sequeda
Juan Sequeda
e36a6c5f10bf558670ec81424012f651b25e23a4
Network-Aware Workload Scheduling for Scalable Linked Data Stream Processing
Network-Aware Workload Scheduling for Scalable Linked Data Stream Processing
In order to cope with the ever-increasing data volume, distributed stream processing systems have been proposed. To ensure scalability most distributed systems partition the data and distribute the workload among multiple machines. This approach does, however, raise the question how the data and the workload should be partitioned and distributed. A uniform scheduling strategy---a uniform distribution of computation load among available machines---typically used by stream processing systems, disregards network-load as one of the major bottlenecks for throughput resulting in an immense load in terms of inter-machine communication. We propose a graph-partitioning based approach for workload scheduling within stream processing systems.We implemented a distributed triple-stream processing engine on top of the Storm realtime computation framework and evaluate its communication behavior using two real-world datasets. We show that the application of graph partitioning algorithms can decrease inter-machine communication substantially (by 40% to 99%) whilst maintaining an even workload distribution, even using very limited data statistics. We also find that processing RDF data as single triples at a time rather than graph fragments (containing multiple triples), may decrease throughput indicating the usefulness of semantics.
Semantic Business Architecture Modelling in Financial Industry Regulation
Semantic Business Architecture Modelling in Financial Industry Regulation
C-SPARQL: A Continuous Extension of SPARQL
Vertical Search Works
Vertical Search Works
NoSQL Databases for RDF: An Empirical Evaluation
NoSQL Databases for RDF: An Empirical Evaluation
Processing large volumes of RDF data requires sophisticated tools. In recent years, much effort was spent on optimizing native RDF stores and on repurposing relational query engines for large-scale RDF processing. Concurrently, a number of new data management systems— regrouped under the NoSQL (for “not only SQL”) umbrella—rapidly rose to prominence and represent today a popular alternative to classical databases. Though NoSQL systems are increasingly used to manage RDF data, it is still difficult to grasp their key advantages and drawbacks in this context. This work is, to the best of our knowledge, the first systematic attempt at characterizing and comparing NoSQL stores for RDF processing. In the following, we describe four different NoSQL stores and compare their key characteristics when running standard RDF benchmarks on a popular cloud infrastructure using both single-machine and distributed deployments.
Axel-Cyrille Ngonga Ngomo
Axel-Cyrille Ngonga Ngomo
3e873fc82e7405de39cb8dc6f2d2c2e445f8c043
D-SPARQ: Distributed, Scalable and Efficient RDF Query Engine
D-SPARQ: Distributed, Scalable and Efficient RDF Query Engine
We present D-SPARQ, a distributed RDF query engine that combines the MapReduce processing framework with a NoSQL distributed data store, MongoDB. The performance of processing SPARQL queries mainly depends on the efficiency of handling the join operations between the RDF triple patterns. Our system features two unique characteristics that enable efficiently tackling this challenge: 1) Identifying specific patterns of the input queries that enable improving the performance by running different parts of the query in a parallel mode. 2) Using the triple selectivity information for reordering the individual triples of the input query within the identified query patterns. The preliminary results demonstrate the scalability and efficiency of our distributed RDF query engine.
SPARQLstream: Ontology-based streaming data access
University of Wollongong
University of Wollongong
Cartic Ramakrishnan
Cartic Ramakrishnan
Hannes Ebner
Hannes Ebner
On Correctness in RDF stream processor benchmarking
On Correctness in RDF stream processor benchmarking
Two complementary benchmarks have been proposed so far for the evaluation and continuous improvement of RDF stream processors: SRBench and LSBench. They put a special focus on different features of the evaluated systems, including coverage of the streaming extensions of SPARQL supported by each processor, query processing throughput, and an early analysis of query evaluation correctness, based on comparing the results obtained by different processors for a set of queries. However, none of them has analysed the operational semantics of these processors in order to assess the correctness of query evaluation results. In this paper, we propose a characterization of the operational semantics of RDF stream processors, adapting well-known models used in the stream processing engine community: CQL and SECRET. Through this formalization, we address correctness in RDF stream processor benchmarks, allowing to determine the multiple answers that systems should provide. Finally, we present CSRBench, an extension of SRBench to address query result correctness verification using an automatic method.
Follow-up Poster Session I
Efficient Computation of Relationship-Centrality in Large Entity-Relationship Graphs
Efficient Computation of Relationship-Centrality in Large Entity-Relationship Graphs
Given two sets of entities – potentially the results of two queries on aknowledge graph like YAGO or DBpedia – characterizing the relationship betweenthese sets in the form of important people, events and organizations is an analyticstask useful in many domains. In this paper, we present an intuitive and efficientlycomputable vertex centrality measure that captures the importance of a nodewith respect to the explanation of the relationship between the pair of query sets.Using a weighted link graph of entities contained in the English Wikipedia, wedemonstrate the usefulness of the proposed measure.
Alessandra Mileo
Alessandra Mileo
25a11e331c48c51344a49c67ffd09a992cfeaf3f
Cinzia Daraio
Cinzia Daraio
06b0e454246a47c93d2777b30a32125baa5d87a7
Ryutaro Ichise
Ryutaro Ichise
Audun Stolpe
Audun Stolpe
Towards Linked Data based Enterprise Information Integration
Gong Cheng
Gong Cheng
90949b51ff990bbe53fa3b030fb31b3c90634551
Akihito Nakamura
Akihito Nakamura
ab7cd41f46e4aad3468c037a84c736e94f2eb9cb
A Hybrid Natural Language Approach to Manage Semantic Interoperability for Public Health Analytics
A Hybrid Natural Language Approach to Manage Semantic Interoperability for Public Health Analytics
This paper discusses the integration of an ontology with a natural language query engine to calculate and interpret epidemiological indicators for population health assessments. In this paper, we discuss the application of this approach to one type of possible query, which retrieves health determinants, causally associated with diabetes mellitus.
L3S Research Center
L3S Research Center
SAP AG
SAP AG
Count Aggregation in Semantic Queries
Count Aggregation in Semantic Queries
Adaptive Semantic Publishing
Korea Institute of Science and Technology Information
Korea Institute of Science and Technology Information
Johannes Trame
Johannes Trame
fbd621d3cabb2870098d2fc706eba5a70baca793
Anupriya Ankolekar
Anupriya Ankolekar
Franck Cotton
Franck Cotton
Towards the Natural Ontology of Wikipedia
Towards the Natural Ontology of Wikipedia
In this paper we present preliminary results on the extraction of ORA: the Natural Ontology of Wikipedia. ORA is obtained through an automatic process that analyses the natural language definitions of DBpedia entities provided by their Wikipedia pages. Hence, this ontology reflects the richness of terms used and agreed by the crowds, and can be updated periodically according to the evolution of Wikipedia.
Edmond Breen
Edmond Breen
13cedb66d04bb342ed1e5332facf887d3485471f
Massimo Paolucci
Massimo Paolucci
Information Reputation
Information Reputation
Introduction
Fluminense Federal University
Fluminense Federal University
seevl.net, MDG Web ltd
seevl.net, MDG Web ltd
Achim Rettinger
Achim Rettinger
Introduction
Mladen Stanojević
Mladen Stanojević
University of Chile
University of Chile
Content and Behaviour Based Metrics for Crowd Truth
Content and Behaviour Based Metrics for Crowd Truth
TBA
Microsoft Research
Microsoft Research
Pat Hayes
Pat Hayes
bd028ef46e23fa534a994760001db850b46bc5f2
University of Toulouse II – Le Mirail
University of Toulouse II – Le Mirail
Christopher Lowis
Christopher Lowis
4f8e414fd43dcb061b7059fca19339e2c08a7446
Developing Crowdsourced Ontology Engineering Tasks: An iterative process
Developing Crowdsourced Ontology Engineering Tasks: An iterative process
Hands-on session
Yanfeng Shu
Yanfeng Shu
Mustafa Jarrar
Mustafa Jarrar
Follow-up Poster Session II
Simon Cox
Simon Cox
Introduction
Yao Shi
Yao Shi
Antonio Corradi
Antonio Corradi
2c493fae9babfa9947dff7d557d6d56569658789
Patrick Paulson
Patrick Paulson
Frame Semantics Annotation Made Easy with DBpedia
Frame Semantics Annotation Made Easy with DBpedia
Achille Fokoue
Achille Fokoue
Follow-up Poster Session III
RDF Data Generation and Publishing
INRIA
INRIA
Using Linked Data for Web scale IE (I)
Mark Molloy
Mark Molloy
91a7155a3c4101746815f51ea5f30dd1fc2e6fde
The Energy Management Adviser at EDF
Karl Aberer
Karl Aberer
a9877790616eb28af52fd602e67b0dbeb50f5399
University of Cambridge
University of Cambridge
Utilising Provenance to Enhance Social Computation
Utilising Provenance to Enhance Social Computation
The effects of Licensing on Open Data: Computing a measure of health for our Scholarly Record
The effects of Licensing on Open Data: Computing a measure of health for our Scholarly Record
As data collections become established in key disciplines, some of the longstanding barriers to data sharing become to dissolve; yet others remain. While metadata and ontologies help overcome the problems of finding and interpreting data, the lack of clarity over licensing remains a real impediment to data reuse. Freedom from legal restriction and uncertainty is essential for the effective sharing, combining and deriving of data from these distributed collections. Reuse and recombination of data will be greatly facilitated by expanding the definition of the semantic web to include the semantics of data licensing. We aim to express licensing terms in a computable manner, within the context of research practice, enabling us to infer the resulting state of rights, obligations and conditions that are inherited by derived and recombined datasets, using a mixed bag of licenses. Building off this we aim to simulate the effects of varying licensing practices within communities, proposing a measure of health of our scholarly record based on compatibility and restrictiveness of the licenses contained therein.
QODI: Query as Context in Automatic Data Integration
QODI: Query as Context in Automatic Data Integration
QODI is an automatic ontology-based data integration system (OBDI). QODI is distinguished in that the ontology mapping algorithm dynamically determines a partial mapping specific to the reformulation of each query. The query provides application context not available in the ontologies alone; thereby the system is able to disambiguate mappings for different queries. The mapping algorithm decomposes the query into a set of paths, and compares the set of paths with a similar decomposition of a source ontology. Using test sets from three real world applications, QODI achieves favorable results compared with AgreementMaker, a leading ontology matcher, and an ontology-based implementation of the mapping methods detailed for Clio, the state-of-the-art relational data integration and data exchange system.
Xiaomin Song
Xiaomin Song
0005a06fa9503f22a2b9183d4c2b4e922a705875
Recommind
Recommind
Infrastructure for Efficient Exploration of Large Scale Linked Data via Contextual Tag Clouds
University of Bristol
University of Bristol
Nadine Steinmetz
Nadine Steinmetz
Conclusions, directions & discussions
Anastasios Kementsietsidis
Anastasios Kementsietsidis
e6563946b9127806c6a94706e6181d5ff2eafc7e
Utilising Provenance to Enhance Social Computation
Utilising Provenance to Enhance Social Computation
Many online platforms employ networks of human workers to perform computational tasks that can be difficult for a machine (e.g. reporting travel disruption). Such systems have to make a range of decisions, for example, selection of suitable workers for a task. In this paper we present an approach that utilises Semantic Web technologies and provenance to support such decision-making processes.
University of Bari
University of Bari
A Graph-Based Approach to Learn Semantic Descriptions of Data Sources
A Graph-Based Approach to Learn Semantic Descriptions of Data Sources
Semantic models of data sources and services provide support to automate many tasks such as source discovery, data integration, and service composition, but writing these semantic descriptions by hand is a tedious and time-consuming task. Most of the related work focuses on automatic annotation with classes or properties of source attributes or input and output parameters. However, constructing a source model that includes the relationships between the attributes in addition to their semantic types remains a largely unsolved problem. In this paper, we present a graph-based approach to hypothesize a rich semantic description of a new target source from a set of known sources that have been modeled over the same domain ontology. We exploit the domain ontology and the known source models to build a graph that represents the space of plausible source descriptions. Then, we compute the top k candidates and suggest to the user a ranked list of the semantic models for the new source. The approach takes into account user corrections to learn more accurate semantic descriptions of future data sources. Our evaluation shows that our method produces models that are twice as accurate than the models produced using a state of the art system that does not learn from prior models.
Stefan Schlobach
Stefan Schlobach
Dennis Thomas
Dennis Thomas
Using Linked Data to evaluate the impact of Research and Development in Europe: a Structural Equation Model
Benjamin Adams
Benjamin Adams
Mobile ontology reasoning
Bo Fu
Bo Fu
0ce7b2d019d67005b671df748f735cb4b6c842d1
Christophe Guéret
Christophe Guéret
c5410a97f81c06006757d2cc8efd8ff3c23ac16f
Max Jakob
Max Jakob
Philipp Frischmuth
Philipp Frischmuth
Carlos Leon
Carlos Leon
Alcatel Lucent Bell Labs
Alcatel Lucent Bell Labs
Daniel Schwabe
Daniel Schwabe
On the Status of Experimental Research on the Semantic Web
On the Status of Experimental Research on the Semantic Web
Experimentation is an important way to validate results of Semantic Web and Computer Science research in general. In this paper, we investigate the development and the current status of experimental work on the Semantic Web. Based on a corpus of 500 papers collected from the International Semantic Web Conferences (ISWC) over the past decade, we analyse the importance and the quality of experimental research conducted and compare it to general Computer Science. We observe that the amount and quality of experiments are steadily increasing over time. Unlike hypothesised, we cannot confirm a statistically significant correlation between a paper’s citations and the amount of experimental work reported. Our analysis, however, shows that papers comparing themselves to other systems are more often cited than other papers.
Evaluating and benchmarking SPARQL query containment solvers
Evaluating and benchmarking SPARQL query containment solvers
Query containment is the problem of deciding if the answers to a query are included in those of another query for any queried database. This problem is very important for query optimization purposes. In the SPARQL context, it can be equally useful. This problem has recently been investigated theoretically and some query containment solvers are available. Yet, there were no benchmarks to compare theses systems and foster their improvement. In order to experimentally assess implementation strengths and limitations, we provide a rst SPARQL containment test benchmark. It has been designed with respect to both the capabilities of existing solvers and the study of typical queries. Some solvers support optional constructs and cycles, while other solvers support pro jection, union of conjunctive queries and RDF Schemas. No solver currently supports all these features or OWL entailment regimes. The study of query demographics on DBPedia logs shows that the vast ma jority of queries are acyclic and a signicant part of them uses UNION or pro jection. We thus test available solvers on their domain of applicability on three dierent benchmark suites. These experiments show that (i) tested solutions are overall functionally correct, (ii) in spite of its complexity, SPARQL query containment is practicable for acyclic queries, (iii) state-of-the-art solvers are at an early stage both in terms of capability and implementation.
Publishing the Norwegian Petroleum Directorate’s FactPages as Semantic Web Data
Anthony Cohn
Anthony Cohn
Amrapali Zaveri
Amrapali Zaveri
77eda3f1f02b4e3244f0e8027bd5655a9ed1716d
Mark B. Sandler
Mark B. Sandler
DAW: Duplicate-AWare Federated Query Processing over the Web of Data
DAW: Duplicate-AWare Federated Query Processing over the Web of Data
Over the last years the Web of Data has developed into a large compendium of interlinked data sets from multiple domains. Due to the decentralised architecture of this compendium, several of these datasets contain duplicated data. Yet, so far, only little attention has been paid to the effect of duplicated data on federated querying. This work presents DAW, a novel duplicate-aware approach to federated querying over the Web of Data. DAW is based on a combination of min-wise independent permutations and compact data summaries. It can be directly combined with existing federated query engines in order to achieve the same query recall values while querying fewer data sources. We extend three well-known federated query processing engines – DARQ, SPLENDID, and FedX – with DAW and compare our extensions with the original approaches. The comparison shows that DAW can greatly reduce the number of queries sent to the endpoints, while keeping high query recall values. Therefore, it can significantly improve the performance of federated query processing engines. Moreover, DAW provides a source selection mechanism that maximises the query recall, when the query processing is limited to a subset of the sources.
Sara Magliacane
Sara Magliacane
d6c1286c440df50c01e55be42e6420f0690bc886
Assessing Content Value for Digital Publishing through Relevance and Provenance-based Trust
Assessing Content Value for Digital Publishing through Relevance and Provenance-based Trust
Due to the abundance of content on the Web, content authors and publishers have a pressing need for systems that select content that is valuable for them, is trustworthy and is related to their own work. Additionally, the value of their own work needs to be assessed before it is published, to guarantee high value for the consumer. In this doctoral research, we investigate how to use Semantic Web technologies to automatically assess the value of content that is – or is about to be – digitally published. To achieve this, we propose methods to assess the relevance of content to existing publications, retrieve or reconstruct its provenance, and derive a trust assessment from this provenance. We discuss our evaluation methods, and present some preliminary results.
Exploring Scholarly Data with Rexplore
Mike Pool
Mike Pool
Faisal Alkhateeb
Faisal Alkhateeb
Eric Charton
Eric Charton
Martin Przyjaciel-Zablocki
Martin Przyjaciel-Zablocki
ec682e0ea5ac9f7506a42e0c6e43e8c693f54149
Eric Franzon
Eric Franzon
Nabil Layaïda
Nabil Layaïda
Marco Neumann
Marco Neumann
Ontology-Based Data Access: Ontop of Databases
Ontology-Based Data Access: Ontop of Databases
We present the architecture and technologies underpinning the OBDA system Ontop and taking full advantage of storing data in relational databases. We discuss the theoretical foundations of Ontop : the tree-witness query rewriting, T -mappings and optimisations based on database integrity constraints and SQL features. We analyse the performance of Ontop in a series of experiments and demonstrate that, for standard ontologies, queries and data stored in relational databases, Ontop is fast, efficient and produces SQL rewritings of high quality.
European Commission - Joint Research Centre
European Commission - Joint Research Centre
Towards a systematic benchmarking of ontology-based query rewriting systems
Towards a systematic benchmarking of ontology-based query rewriting systems
Query rewriting is one of the fundamental steps in ontologybased data access (OBDA) approaches. It takes as inputs an ontology and a query written according to that ontology, and produces as an output a set of queries that should be evaluated to account for the inferences that should be considered for that query and ontology. Different query rewriting systems give support to different ontology languages with varying expressiveness, and the rewritten queries obtained as an output do also vary in expressiveness. This heterogeneity has traditionally made it difficult to compare different approaches, and the area lacks in general commonly agreed benchmarks that could be used not only for such comparisons but also for improving OBDA support. In this paper we compile data, dimensions and measurements that have been used to evaluate some of the most recent systems, we analyse and characterise these assets, and provide a unified set of them that could be used as a starting point towards a more systematic benchmarking process for such systems. Finally, we apply this initial benchmark with some of the most relevant OBDA approaches in the state of the art.
Jorge Gracia
Jorge Gracia
Derivo GmbH
Derivo GmbH
Esteban García-Cuesta
Esteban García-Cuesta
78b1fe161d50b146eeb8120cb213fdf31cd3fb60
Chiara Del Vescovo
Chiara Del Vescovo
bb1fd9fa5c984fb7033c7a2c9a6b980ab3b46714
Knowledge Graph Identification
Knowledge Graph Identification
Large-scale information processing systems are able to extract massive collections of interrelated facts, but unfortunately transforming these candidate facts into useful knowledge is a formidable challenge. In this paper, we show how uncertain extractions about entities and their relations can be transformed into a know ledge graph. The extractions form an extraction graph and we refer to the task of removing noise, inferring missing information, and determining which candidate facts should be included into a knowledge graph as know ledge graph identification. In order to perform this task, we must reason jointly about candidate facts and their associated extraction confidences, identify coreferent entities, and incorporate ontological constraints. Our proposed approach uses probabilistic soft logic (PSL), a recently introduced probabilistic modeling framework which easily scales to millions of facts. We demonstrate the power of our method on a synthetic Linked Data corpus derived from the MusicBrainz music community and a real-world set of extractions from the NELL pro ject containing over 1M extractions and 70K ontological relations. We show that compared to existing methods, our approach is able to achieve improved AUC and F1 with significantly lower running time.
Fabiana Kubke
Fabiana Kubke
Evaluation measures for ontology matchers in supervised matching scenarios
Evaluation measures for ontology matchers in supervised matching scenarios
Precision and Recall, as well as their combination in terms of F-Measure, are widely used measures in computer science and generally applied to evaluate the overall performance of ontology matchers in fully automatic, unsupervised scenarios. In this paper, we investigate the case of supervised matching, where automatically created ontology alignments are verified by an expert. We motivate and describe this use case and its characteristics and discuss why traditional, F-measure based evaluation measures are not suitable for this use case. Therefore, we investigate several alternative evaluation measures and propose the use of Precision@N curves as a mean to assess different matching systems for supervised matching. We compare the ranking of several state of the art matchers using Precision@N curves to the traditional F-measure based ranking, and discuss means to combine matchers in a way that optimizes the user support in supervised ontology matching.
Myung-Jae Park
Myung-Jae Park
25e4237b8e8b4fd1f5fe9536ae88478970dafac9
Nicolas Torzec
Nicolas Torzec
3462943af3f6239c92dac16a2dd6f3b7011c1437
David Corsar
David Corsar
2b7afd78591fd22e3723beedf01577ee1e826987
Chetana Gavankar
Chetana Gavankar
e0a256306b228712f1e0f37eb0115e5f70faf13f
Anca Dumitrache
Anca Dumitrache
Geographica: A Benchmark for Geospatial RDF Stores
Geographica: A Benchmark for Geospatial RDF Stores
Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores.
IncMap: Pay as you go Matching of Relational Schemata to OWL Ontologies
What's in a 'nym'? Synonyms in Biomedical Ontology Matching
What's in a 'nym'? Synonyms in Biomedical Ontology Matching
To bring the Life Sciences domain closer to a Semantic Web realization it is fundamental to establish meaningful relations between biomedical ontologies. The successful application of ontology matching techniques is strongly tied to an effective exploration of the complex and diverse biomedical terminology contained in biomedical ontologies. In this paper, we present an overview of the lexical components of several biomedical ontologies and investigate how different approaches for their use can impact the performance of ontology matching techniques. We propose novel approaches for exploring the different types of synonyms encoded by the ontologies and for extending them based both on internal synonym derivation and on external ontologies. We evaluate our approaches using AgreementMaker, a successful ontology matching platform that implements several lexical matchers, and apply them to a set of four benchmark biomedical ontology matching tasks. Our results demonstrate the impact that an adequate consideration of ontology synonyms can have on matching performance, and validate our novel approach for combining internal and external synonym sources as a competitive and in many cases improved solution for biomedical ontology matching.
William Cohen
William Cohen
c4a2e67b44dd01c9fefddab1bdc2cd7840e64fda
Marco Antonio Casanova
Marco Antonio Casanova
9276cf3412de9c333bd6357ba277841df8d03c67
Srikanta J. Bedathur
Srikanta J. Bedathur
b5f902dd9ef208299c99b1d727fddf1b963490ee
Complete Query Answering Over Horn Ontologies Using a Triple Store
Paul Alexander
Paul Alexander
e4532edb374cb842d2bf282fc686bcb43b79833c
Andreas Hotho
Andreas Hotho
Introducing Statistical Design of Experiments to SPARQL Endpoint Evaluation
Introducing Statistical Design of Experiments to SPARQL Endpoint Evaluation
This paper argues that the common practice of benchmarking is inadequate as a scientific evaluation methodology. It further attempts to introduce the empirical tradition of the physical sciences by using techniques from Statistical Design of Experiments applied to the example of SPARQL endpoint performance evaluation. It does so by studying full as well as fractional factorial experiments designed to evaluate an assertion that some change introduced in a system has improved performance. This paper does not present a finished experimental design, rather its main focus is didactical, to shift the focus of the community away from benchmarking towards higher scientific rigor.
Complex correspondences for query patterns rewriting
Type Inference on Noisy RDF Data
Type Inference on Noisy RDF Data
Type information is very valuable in knowledge bases. However, most large open knowledge bases are incomplete with respect to type information, and, at the same time, contain noisy and incorrect data. That makes classic type inference by reasoning difficult. In this paper, we propose the heuristic link-based type inference mechanism SD-Type, which can handle noisy and incorrect data. Instead of leveraging T-box information from the schema, SDType takes the actual use of a schema into account and thus is also robust to misused schema elements.
Towards Vagueness-Aware Ontologies
Albert Haque
Albert Haque
a69c8d52c52d0cfbdabc2e7edd638dd14cc137b3
A Semantic Lab Notebook – Report on a Use Case Modelling an Experiment of a Microwave-based Quarantine Method
A Semantic Lab Notebook – Report on a Use Case Modelling an Experiment of a Microwave-based Quarantine Method
Zolzaya Dashdorj
Zolzaya Dashdorj
56b0753e26ff46c9b275516ed2b6d1aeb382efe9
Matthew Gamble
Matthew Gamble
Linked Data 1
Welcome
Infrastructure for Efficient Exploration of Large Scale Linked Data via Contextual Tag Clouds
Infrastructure for Efficient Exploration of Large Scale Linked Data via Contextual Tag Clouds
In this paper we present the infrastructure of the contextual tag cloud system which can execute large volumes of queries about the number of instances that use particular ontological terms. The contextual tag cloud system is a novel application that helps users explore a large scale RDF dataset: the tags are ontological terms (classes and properties), the context is a set of tags that defines a subset of instances, and the font sizes reflect the number of instances that use each tag. It visualizes the patterns of instances specified by the context a user constructs. Given a request with a specific context, the system needs to quickly find what other tags the instances in the context use, and how many instances in the context use each tag. The key question we answer in this paper is how to scale to Linked Data; in particular we use a dataset with 1.4 billion triples and over 380,000 tags. This is complicated by the fact that the calculation should, when directed by the user, consider the entailment of taxonomic and/or domain/range axioms in the ontology. We combine a scalable preprocessing approach with a specially-constructed inverted index and use three approaches to prune unnecessary counts for faster intersection computations. We compare our system with a state-of-the-art triple store, examine how pruning rules interact with inference and analyze our design choices.
University of Trento
University of Trento
University of Zaragoza
University of Zaragoza
University of Economics
University of Economics
Detecting Good Practices and Pitfalls when Publishing Vocabularies on the Web
Event Processing in RDF
Handling uncertainty in semantic information retrieval process
Mihajlo Pupin Institute
Mihajlo Pupin Institute
Herbert van de Sompel
Herbert van de Sompel
Building Exceutable Biological Pathway Models Automatically from BioPAX
Building Exceutable Biological Pathway Models Automatically from BioPAX
Martin G. Skjæveland
Martin G. Skjæveland
5223e81829088aa837295fab98f3c286b8f106a2
Marco Luca Sbodio
Marco Luca Sbodio
577eb4f75845c4576b906544c29f5b4a729fb465
Discovering Missing Semantic Relations between Entities in Wikipedia
Discovering Missing Semantic Relations between Entities in Wikipedia
Wikipedia’s infoboxes contain rich structured information of various entities, which have been explored by the DBpedia pro ject to generate large scale Linked Data sets. Among all the infobox attributes, those attributes having hyperlinks in its values identify semantic relations between entities, which are important for creating RDF links between DBpedia’s instances. However, quite a few hyperlinks have not been anotated by editors in infoboxes, which causes lots of relations between entities being missing in Wikipedia. In this paper, we propose an approach for automatically discovering the missing entity links in Wikipedia’s infoboxes, so that the missing semantic relations between entities can be established. Our approach first identifies entity mentions in the given infoboxes, and then computes several features to estimate the possibilities that a given attribute value might link to a candidate entity. A learning model is used to obtain the weights of different features, and predict the destination entity for each attribute value. We evaluated our approach on the English Wikipedia data, the experimental results show that our approach can effectively find the missing relations between entities, and it significantly outperforms the baseline methods in terms of both precision and recall.
Josiane Xavier Parreira
Josiane Xavier Parreira
a69a534c7a5802053569792e8c769d8981487eb4
Reasoning Performance Indicators for Ontology Design Patterns
Arofan Gregory
Arofan Gregory
Using Semantic Web Technologies to Reproduce a Pharmacovigilance Case Study
Using Semantic Web Technologies to Reproduce a Pharmacovigilance Case Study
Glenn Wightwick
Glenn Wightwick
Gilson Libório Mendes
Gilson Libório Mendes
DynamiTE: Parallel Materialization of Dynamic RDF Data
DynamiTE: Parallel Materialization of Dynamic RDF Data
One of the main advantages of using semantically annotated data is that machines can reason on it, deriving implicit knowledge from explicit information. In this context, materializing every possible implicit derivation from a given input can be computationally expensive, especially when considering large data volumes. Most of the solutions that address this problem rely on the assumption that the information is static, i.e., that it does not change, or changes very infrequently. However, the Web is extremely dynamic: online newspapers, blogs, social networks, etc., are frequently changed so that outdated information is removed and replaced with fresh data. This demands for a materialization that is not only scalable, but also reactive to changes. In this paper, we consider the problem of incremental materialization, that is, how to update the materialized derivations when new data is added or removed. To this purpose, we consider the ρdf RDFS fragment [12], and present a parallel system that implements a number of algorithms to quickly recalculate the derivation. In case new data is added, our system uses a parallel version of the well-known semi-naive evaluation of Datalog. In case of removals, we have implemented two algorithms, one based on previous theoretical work, and another one that is more efficient since it does not require a complete scan of the input. We have evaluated the performance using a prototype system called DynamiTE , which organizes the knowledge bases with a number of indices to facilitate the query process and exploits parallelism to improve the performance. The results show that our methods are indeed capable to recalculate the derivation in a short time, opening the door to reasoning on much more dynamic data than is currently possible.
OM-2013 Morning Tea / Poster session
Fang Wei-Kleiner
Fang Wei-Kleiner
Statistical Knowledge Patterns for Characterising Linked Data
Antony Williams
Antony Williams
3e8c20a7e0ede14deef4ccd0c1280b233be7899a
Beijing Normal University
Beijing Normal University
Eric Stephan
Eric Stephan
A Checklist-Based Approach for Quality Assessment of Scientific Information
A Checklist-Based Approach for Quality Assessment of Scientific Information
Timothy Lebo
Timothy Lebo
cdecab02f3fb1d3d9c79e1a8a8730bd11ef9f2d3
Frank De Bakker
Frank De Bakker
Prajit Das
Prajit Das
TRank: Ranking Entity Types Using the Web of Data
TRank: Ranking Entity Types Using the Web of Data
Much of Web search and browsing activity is today centered around entities. For this reason, Search Engine Result Pages (SERPs) increasingly contain information about the searched entities such as pictures, short summaries, related entities, and factual information. A key facet that is often displayed on the SERPs and that is instrumental for many applications is the entity type. However, an entity is usually not associated to a single generic type in the background knowledge bases but rather to a set of more specific types, which may be relevant or not given the document context. For example, one can find on the Linked Open Data cloud the fact that Tom Hanks is a person, an actor, and a person from Concord, California. All those types are correct but some may be too general to be interesting (e.g., person), while other may be interesting but already known to the user (e.g., actor), or may be irrelevant given the current browsing context (e.g., person from Concord, California). In this paper, we define the new task of ranking entity types given an entity and its context. We propose and evaluate new methods to find the most relevant entity type based on collection statistics and on the graph structure interconnecting entities and types. An extensive experimental evaluation over several document collections at different levels of granularity (e.g., sentences, paragraphs, etc.) and different type hierarchies (including DBPedia, Freebase, and schema.org) shows that hierarchy-based approaches provide more accurate results when picking entity types to be displayed to the end-user while still being highly scalable.
Kavi Mahesh
Kavi Mahesh
7cc023d4132fafa4ab5e155b8fb639ada62bece3
University of Texas at Austin
University of Texas at Austin
Timea Bagosi
Timea Bagosi
ff7e51feb20a2cfc97f0aaf90058bff9bdc20a23
Ontology Patterns: Clarifying Concepts and Terminology
Serena Villata
Serena Villata
200fa053a13df35295f805b07e244b0922bb0010
Capturing intent and rationale for Linked Science: design patterns as a resource for linked laboratory experiments
Capturing intent and rationale for Linked Science: design patterns as a resource for linked laboratory experiments
CrowdSen Session 4
Ritaban Dutta
Ritaban Dutta
Hans Uszkoreit
Hans Uszkoreit
288ac7498712bfe804d7abf3637e67947fa188e0
Doctoral Consortium Welcome
Using Semantic Web in ICD-11: Three Years Down the Road
University of Maryland, Baltimore County
University of Maryland, Baltimore County
Soonho Kim
Soonho Kim
Data Archiving and Networked Services (DANS)
Data Archiving and Networked Services (DANS)
CrowdSem Session 3
Steffen Staab
Steffen Staab
Exploiting Semantics from Ontologies and Shared Annotations to Find Patterns in Annotated Linked Open Data
Exploiting Semantics from Ontologies and Shared Annotations to Find Patterns in Annotated Linked Open Data
Kingsley Idehen
Kingsley Idehen
Ba Lam Do
Ba Lam Do
University of Wisconsin–Madison
University of Wisconsin–Madison
Alfio Ferrara
Alfio Ferrara
Arkady Zaslavsky
Arkady Zaslavsky
9a1c7923259025c1ab09310b5e766107a738f177
Semantic Data and Models Sharing in systems Biology: The Just Enough Results Model and the SEEK Platform
Dominik Benz
Dominik Benz
Connected Discovery
Connected Discovery
Nile University
Nile University
SPARQL Web-Querying Infrastructure: Ready for Action?
SPARQL Web-Querying Infrastructure: Ready for Action?
Hundreds of public SPARQL endpoints have been deployed on the Web, forming a novel decentralised infrastructure for querying billions of structured facts from a variety of sources on a plethora of topics. But is this infrastructure mature enough to support applications? For 427 public SPARQL endpoints registered on the DataHub, we conduct various experiments to test their maturity. Regarding discoverability, we nd that only one-third of endpoints make descriptive meta-data available, making it dicult to locate or learn about their content and capabilities. Regarding interoperability, we nd patchy support for established SPARQL features like ORDER BY as well as (understandably) for new SPARQL 1.1 features. Regarding eciency, we show that the performance of endpoints for generic queries can vary by up to 34 orders of magnitude. Regarding availability, based on a 27-month long monitoring experiment, we show that only 32.2% of public endpoints can be expected to have (monthly) two-nines uptimes of 99100%.
Dimitris Plexousakis
Dimitris Plexousakis
Konstantinos Papangelis
Konstantinos Papangelis
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Simone Tallevi-Diotallevi
Simone Tallevi-Diotallevi
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Johannes Knopp
Johannes Knopp
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Daniel Faria
Daniel Faria
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John S. Tyssedal
John S. Tyssedal
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Iván Cantador
Iván Cantador
Tudor Groza
Tudor Groza
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Amal Zouaq
Amal Zouaq
String Similarity Metrics for Ontology Alignment
String Similarity Metrics for Ontology Alignment
Ontology alignment is an important part of enabling the semantic web to reach its full potential. The vast ma jority of ontology alignment systems use one or more string similarity metrics, but often the choice of which metrics to use is not given much attention. In this work we evaluate a wide range of such metrics, along with string pre-processing strategies such as removing stop words and considering synonyms, on different types of ontologies. We also present a set of guidelines on when to use which metric. We furthermore show that if optimal string similarity metrics are chosen, those alone can produce alignments that are competitive with the state of the art in ontology alignment systems. Finally, we examine the improvements possible to an existing ontology alignment system using an automated string metric selection strategy based upon the characteristics of the ontologies to be aligned.
Willem van Hage
Willem van Hage
BiographyNet: Managing Provenance at multiple levels and from different perspectives
BiographyNet: Managing Provenance at multiple levels and from different perspectives
Panos Alexopoulos
Panos Alexopoulos
Wolf Siberski
Wolf Siberski
Evangelos Kalampokis
Evangelos Kalampokis
Microtask crowdsourcing fundamentals
Varish Mulwad
Varish Mulwad
b9885e735b09d1c4e49215927f8b2dde8bac5a2c
Mariano Rodriguez-Muro
Mariano Rodriguez-Muro
9834233dbc9d00654ac36e085f897a38c1a88df3
Katja Hose
Katja Hose
Microsoft
Microsoft
Arupa Sarkar
Arupa Sarkar
Seevl
Seevl
Scalable Linked Data Stream Processing via Network-Aware Workload Scheduling
Scalable Linked Data Stream Processing via Network-Aware Workload Scheduling
Claude Bernard University Lyon 1
Claude Bernard University Lyon 1
Cliff Joslyn
Cliff Joslyn
Fadi Maali
Fadi Maali
Universidade Federal do Espírito Santo
Universidade Federal do Espírito Santo
Jose-Emilio Labra Gayo
Jose-Emilio Labra Gayo
A Distributed Directory System
A Distributed Directory System
Memect
Memect
Elizabeth K. Bowman
Elizabeth K. Bowman
Wolf-Tilo Balke
Wolf-Tilo Balke
45c7502d75b8c733cb58d96a3eb6d22c9f304623
Yuzhang Feng
Yuzhang Feng
José Enrique Ruiz
José Enrique Ruiz
6544eecb18b80f62483254e55c1a7b4824f6c355
Csaba Veres
Csaba Veres
Steffen Stadtmüller
Steffen Stadtmüller
Alessandra Sala
Alessandra Sala
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Raghava Mutharaju
Raghava Mutharaju
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Wantian Ke
Wantian Ke
f21b9e4c7318aeec9e4c067ef70aa650708a92c2
Vassilis Christophides
Vassilis Christophides
Paolo Bouquet
Paolo Bouquet
LD4IE - Linked Data for Information Extraction
Olivier Curé
Olivier Curé
33cd62b318bd504dde9eea1cdcf0095394e4ba40
Exploring Linked Open Data with Tag Clouds
Exploring Linked Open Data with Tag Clouds
In this paper we present the contextual tag cloud system: a novel application that helps users explore a large scale RDF dataset. Unlike folksonomy tags used in most traditional tag clouds, the tags in our system are ontological terms (classes and properties), and a user can construct a context with a set of tags that defines a subset of instances. Then in the contextual tag cloud, the font size of each tag depends on the number of instances that are associated with that tag and all tags in the context. Each contextual tag cloud serves as a summary of the distribution of relevant data, and by changing the context, the user can quickly gain an understanding of patterns in the data. Furthermore, the user can choose to include RDFS taxonomic and/or domain/range entailment in the calculations of tag sizes, thereby understanding the impact of semantics on the data. The system runs on the BTC2012 dataset with more than 1.4 billion triples from which we extract over 380,000 tags. Several scalability challenges must be overcome in order to achieve a responsive interface.
Christoph Pinkel
Christoph Pinkel
77399f7516b596a8967dd6e41d31de0e66f07846
Jennifer Vendetti
Jennifer Vendetti
5b4bd5a5a744e869856c7c22d4b9608e16dad23c
Autonomous Province of Trento
Autonomous Province of Trento
Publishing Data from the Smithsonian American Art Museum as Linked Open Data
Publishing Data from the Smithsonian American Art Museum as Linked Open Data
Museums around the world have built databases with meta-data about millions of objects, their history, the people who created them, and the entities they represent. This data is stored in proprietary databases and is not readily available for use. Recently, museums embraced the Semantic Web as a means to make this data available to the world, but the experience so far shows that publishing museum data to the linked data cloud is difficult: the databases are large and complex, the information is richly structured and varies from museum to museum, and it is difficult to link the data to other datasets. We have been collaborating with the Smithsonian American Art Museum to create a set of tools that allow museums and other cultural heritage institutions to publish their data as Linked Open Data. In this demonstration we will show the end-to-end process of starting with the original source data, modeling the data with respect to a ontology of cultural heritage data, linking the data to DBpedia, and then publishing the information as Linked Open Data. Video: http://youtu.be/1Vaytr09H1w
Paper presentations I
DistEL: A Distributed EL+ Ontology Classifier
DistEL: A Distributed EL+ Ontology Classifier
Daniele Dell'Aglio
Daniele Dell'Aglio
0368c2729baee1c7bb64b14e81c329613f33b967
Hasso Plattner Institute
Hasso Plattner Institute
Paper Presentations III
GRAPHIUM: Visualizing Performance of Graph and RDF Engines on Linked Data
GRAPHIUM: Visualizing Performance of Graph and RDF Engines on Linked Data
We present GRAPHIUM a tool to visualize trends and patterns in the performance of existing graph and RDF engines. We will demonstrate GRAPHIUM and attendees will be able to observe and analyze the performance exhibited by Neo4j, DEX, HypergraphDB and RDF-3x when core graph-based and mining tasks are run against a variety of benchmark of graphs of diverse characteristics.
Argumentation-based Inconsistencies Detection for Question-Answering over DBpedia
Jong-Ryul Lee
Jong-Ryul Lee
a067f7bb4fe43039b9c308dc7a215c827af7ceef
Fernando Bobillo
Fernando Bobillo
Paper Presentations II
Gerd Gröner
Gerd Gröner
0b39da82cd110b143beb5837931d01f0bdf4c60c
University of Waterloo
University of Waterloo
Rule-based Reasoning on Massively Parallel Hardware
Rule-based Reasoning on Massively Parallel Hardware
Raymond Fergerson
Raymond Fergerson
65489881169b183cca31c3df9411620e6ca719eb
Apolinar Figueroa
Apolinar Figueroa
University of Southampton
University of Southampton
SILURIAN: a Sparql vIsuaLizer for UndeRstanding querIes And federatioNs
SILURIAN: a Sparql vIsuaLizer for UndeRstanding querIes And federatioNs
SPARQL federated queries can be affected by both characteristics of the query and datasets in the federation. We present SILURIAN a Sparql vIsuaLizer for UndeRstanding querIes And federatioNs. SILURIAN visualizes SPARQL queries and, thus, it allows the analysis and understanding of a query complexity with respect to relevant endpoints and shapes of the possible plans.
Technical University of Madrid
Technical University of Madrid
Dongsheng Zhang
Dongsheng Zhang
Paulo Pinheiro da Silva
Paulo Pinheiro da Silva
Katherine Chastain
Katherine Chastain
2b80575d883ddec4ad117fe27b0c9d5461ada915
Pierre-Yves Vandenbussche
Pierre-Yves Vandenbussche
4d190ad7bf441f2c9a4885751c3fa65a85110661
John Howse
John Howse
TripleRush: A Fast and Scalable Triple Store
TripleRush: A Fast and Scalable Triple Store
University of New England (Australia)
University of New England (Australia)
Crowd-sourced semantics
University of Ulm
University of Ulm
Optimizing RDF stores by coupling General-purpose Graphics Processing Units and Central Processing Units
Optimizing RDF stores by coupling General-purpose Graphics Processing Units and Central Processing Units
Using BabelNet in Bridging the Gap Between Natural Language Queries and Linked Data Concepts
Modeling and Reasoning Upon Facebook Privacy Settings
Modeling and Reasoning Upon Facebook Privacy Settings
Understanding the way information is propagated and made visible on Facebook is a difficult task. The privacy settings and the rules that apply to individual items are reasonably straightforward. However, for the user to track all of the information that needs to be integrated and the inferences that can be made on their posts is complex, to the extent that it is almost impossible for any individual to achieve. In this demonstration, we investigate the use of knowledge modeling and reasoning techniques (including basic ontological representation, rules and epistemic logics) to make these inferences explicit to the user.
National Institute of Informatics
National Institute of Informatics
Tristan O'Neilla
Tristan O'Neilla
Enriching Ontologies through Data
Enriching Ontologies through Data
Eviction Strategies for Semantic Flow Processing
Eviction Strategies for Semantic Flow Processing
École Centrale Paris
École Centrale Paris
Statistical Analyses of Named Entity Disambiguation Benchmarks
Licensing and Confidentiality Models
Explaining data patterns using background knowledge from Linked Data
Explaining data patterns using background knowledge from Linked Data
Manuel Atencia
Manuel Atencia
Comparing ontologies with ecco
Comparing ontologies with ecco
The detection and presentation of changes between OWL ontologies (in the form of a diff) is an important service for ontology engineering, being an active research topic. We present here a diff tool that incorporates structural and semantic techniques in order to, firstly, distinguish effectual and ineffectual changes between ontologies and, secondly, align and categorise those changes according to their impact. Such a categorisation of changes is shown to facilitate the navigation through, and analysis of change sets. The tool is made available as a web-based application, as well as a standalone command-line tool. Both of these output an XML change set file and a transformation into HTML, which allows users to browse through and focus on those changes of utmost interest using any web-browser.
Jing Sun
Jing Sun