Tom Heath

Bio: Tom Heath is an academic researcher from Open Data Institute. The author has contributed to research in topics: Semantic Web & Social Semantic Web. The author has an hindex of 20, co-authored 41 publications receiving 8847 citations. Previous affiliations of Tom Heath include Open University.

Linked Data - the story so far

Abstract: The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

Linked Data: Evolving the Web into a Global Data Space

Abstract: The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.

How to Publish Linked Data on the Web - Proposal for a Half-day Tutorial at ISWC2008

Abstract: The Web is increasingly understood as a global information space consisting not just of linked documents, but also of Linked Data. The Linked Data principles provide a basis for realizing this Web of Data, or Semantic Web. Since early 2007 numerous data sets have been published on the Web according to these principles, in domains as broad as music, books, geographical information, films, people, events, reviews and photos. In combination these data sets consist of over 2 billion RDF triples, interlinked by more than 3 million triples that cross data sets. As this Web of Linked Data continues to grow, and an increasing number of applications are developed that exploit these data sets, there is a growing need for data publishers, researchers, developers and Web practitioners to understand Linked Data principles and practice. Run by some of the leading members of the Linked Data community, this tutorial will address those needs, and provide participants with a solid foundation from which to begin publishing Linked Data on the Web, as well as to implement applications that consume Linked Data from the Web.

Linked data on the web (LDOW2008)

Abstract: The Web is increasingly understood as a global information space consisting not just of linked documents, but also of Linked Data. More than just a vision, the resulting Web of Data has been brought into being by the maturing of the Semantic Web technology stack, and by the publication of an increasing number of datasets according to the principles of Linked Data.The Linked Data on the Web (LDOW2008) workshop brings together researchers and practitioners working on all aspects of Linked Data. The workshop provides a forum to present the state of the art in the field and to discuss ongoing and future research challenges. In this workshop summary we will outline the technical context in which Linked Data is situated, describe developments in the past year through initiatives such as the Linking Open Data community project, and look ahead to the workshop itself.

The Semantic Web - ISWC 2009

Abstract: Research Track.- Queries to Hybrid MKNF Knowledge Bases through Oracular Tabling.- Automatically Constructing Semantic Web Services from Online Sources.- Exploiting User Feedback to Improve Semantic Web Service Discovery.- A Generic Approach for Large-Scale Ontological Reasoning in the Presence of Access Restrictions to the Ontology's Axioms.- OntoCase-Automatic Ontology Enrichment Based on Ontology Design Patterns.- Graph-Based Ontology Construction from Heterogenous Evidences.- DOGMA: A Disk-Oriented Graph Matching Algorithm for RDF Databases.- Semantically-Aided Business Process Modeling.- Task Oriented Evaluation of Module Extraction Techniques.- A Decomposition-Based Approach to Optimizing Conjunctive Query Answering in OWL DL.- Goal-Directed Module Extraction for Explaining OWL DL Entailments.- Analysis of a Real Online Social Network Using Semantic Web Frameworks.- Coloring RDF Triples to Capture Provenance.- TripleRank: Ranking Semantic Web Data by Tensor Decomposition.- What Four Million Mappings Can Tell You about Two Hundred Ontologies.- Modeling and Query Patterns for Process Retrieval in OWL.- Context and Domain Knowledge Enhanced Entity Spotting in Informal Text.- Using Naming Authority to Rank Data and Ontologies for Web Search.- Executing SPARQL Queries over the Web of Linked Data.- Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes.- Decidable Order-Sorted Logic Programming for Ontologies and Rules with Argument Restructuring.- Semantic Web Service Composition in Social Environments.- XLWrap - Querying and Integrating Arbitrary Spreadsheets with SPARQL.- Optimizing QoS-Aware Semantic Web Service Composition.- Synthesizing Semantic Web Service Compositions with jMosel and Golog.- A Practical Approach for Scalable Conjunctive Query Answering on Acyclic Knowledge Base.- Learning Semantic Query Suggestions.- Investigating the Semantic Gap through Query Log Analysis.- Towards Lightweight and Robust Large Scale Emergent Knowledge Processing.- On Detecting High-Level Changes in RDF/S KBs.- Efficient Query Answering for OWL 2.- Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data.- A Conflict-Based Operator for Mapping Revision.- Functions over RDF Language Elements.- Policy-Aware Content Reuse on the Web.- Exploiting Partial Information in Taxonomy Construction.- Actively Learning Ontology Matching via User Interaction.- Optimizing Web Service Composition While Enforcing Regulations.- A Weighted Approach to Partial Matching for Mobile Reasoning.- Scalable Distributed Reasoning Using MapReduce.- Discovering and Maintaining Links on the Web of Data.- Concept and Role Forgetting in Ontologies.- Parallel Materialization of the Finite RDFS Closure for Hundreds of Millions of Triples.- Semantic Web In Use.- Live Social Semantics.- RAPID: Enabling Scalable Ad-Hoc Analytics on the Semantic Web.- LinkedGeoData: Adding a Spatial Dimension to the Web of Data.- Enrichment and Ranking of the YouTube Tag Space and Integration with the Linked Data Cloud.- Produce and Consume Linked Data with Drupal!.- Extracting Enterprise Vocabularies Using Linked Open Data.- Reasoning about Resources and Hierarchical Tasks Using OWL and SWRL.- Using Hybrid Search and Query for E-discovery Identification.- Bridging the Gap between Linked Data and the Semantic Desktop.- Vocabulary Matching for Book Indexing Suggestion in Linked Libraries - A Prototype Implementation and Evaluation.- Semantic Web Technologies for the Integration of Learning Tools and Context-Aware Educational Services.- Semantic Enhancement for Enterprise Data Management.- Lifting Events in RDF from Interactions with Annotated Web Pages.- A Case Study in Integrating Multiple E-commerce Standards via Semantic Web Technology.- Supporting Multi-view User Ontology to Understand Company Value Chains.- Doctoral Consortium.- EXPRESS: EXPressing REstful Semantic Services Using Domain Ontologies.- A Lexical-Ontological Resource for Consumer Heathcare.- Semantic Web for Search.- Towards Agile Ontology Maintenance.- Ontologies for User Interface Integration.- Semantic Usage Policies for Web Services.- Ontology-Driven Generalization of Cartographic Representations by Aggregation and Dimensional Collapse.- Invited Talks.- Populating the Semantic Web by Macro-reading Internet Text.- Search 3.0: Present, Personal, Precise.

Linked Data - the story so far

Abstract: The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

DBpedia: a nucleus for a web of open data

Abstract: DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human-andmachine-consumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

Wikidata: a free collaborative knowledgebase

Abstract: This collaboratively edited knowledgebase provides a common source of data for Wikipedia, and everyone else.

Ontology Matching

Abstract: Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.