Towards Ontology Mapping: DL View or Graph View?

Ontology is important in sharing and reusing knowledge. It also plays a crucial role in the development of Semantic Web. The paper discusses the DL(Description Logic) and graph view on ontology. Different perspectives have different models and approaches on ontology mapping. The paper presents how the two different approaches handle ontology mapping, respectively. We argue that a combination of the two views can lead to a better solution in ontology mapping

Translating expressive ontology mappings into rewriting rules to implement query rewriting

The increasing amount of structured RDF data published by the Linked Data community poses a great challenge when it comes to reconcile heterogeneous schemas adopted by data publishers. For several years, the Semantic Web community has been developing algorithms for aligning data models (ontologies). Nevertheless, exploiting such ontology alignments for achieving data integration is still an under supported research topic. The semantics of ontology alignments, often defined over a logical framework, implies a reasoning step over huge amounts of data. This is often hard to implement and rarely scales on Web dimensions. This paper presents our approach for translating DL-like ontology alignments into graph patterns that can be used to implement ontological mediation in the form of SPARQL query rewriting and generation. This approach backs up a previous work for achieving SPARQL query rewriting where syntactical transformations of basic graph patterns are used. Supporting a rich ontology alignment language into our system is important for two reasons. Firstly the users can express rich alignments focusing on their semantic soundness; secondly more verbose correspondences of RDF patterns can be generated by the translation process providing a denotational semantics to the alignment language itself. The approach has been implemented into an open source Java API freely available to the community

Web Science emerges

The relentless rise in Web pages and links is creating emergent properties, from social networks to virtual identity theft, that are transforming society. A new discipline, Web Science, aims to discover how Web traits arise and how they can be harnessed or held in check to benefit society. Important advances are beginning to be made; more work can solve major issues such as securing privacy and conveying trust

Foundations of Web Science: Introductory Lecture 2. What is Web Science?

Professor Nigel Shadbolt describes the emergence of Web Science Research Initiative and discusses the themes and topics that contribute to an understanding of Web Science

Open Government Data: Making it Real??

This talk will review our successes in Open Government Data and why it is so important to us all. It will include a frank discussion of the problems encountered and the challenges that lay ahead. Problems and challenges that will be much more tractable if we work together. It will also detail some key requirements around policy and technology to ensure the efforts can scale and complement each other. It also encourages the Open Data Community to makes its voice heard in the various national consultations underway

Ontologies Change and Queries Break: Towards a Solution

Keeping track of ontology changes is becoming a critical issue for ontology-based applications. Updating an ontology that is in use may result in inconsistencies between the ontology and the knowledge base, dependent ontologies and applications/services. Current research concentrates on the creation of ontologies and how to manage ontology changes in terms of mapping ontology versions and keeping consistent with the instances. Very little work investigated controlling the impact on dependent applications/services; which is the aim of the system presented in this paper. The approach we propose is to make use of ontology change logs to analyse incoming RDQL queries and amend them as necessary. Revised queries can then be used to query the ontology and knowledge base as requested by the applications and services. We describe the design of our prototype system, and discuss related problems and future directions

Change Management: The Core Task of Ontology Versioning and Evolution

Change management as a key issue in ontology versioning and evolution is still not fully addressed, which to some extent forms a barrier against the smooth process of ontology evolution. The key issue in the support of evolving ontologies is to distinguish and recognize the changes during the process of ontology evolution. Most of the current popular work on ontology versioning do not keep a record of the changes in the ontology, thus preventing the user from tracking those changes back and forward, or to at least understand the rational behind those changes. We are proposing an approach to get the evidences of ontology changes, keep track of them, and manage them in an engineering fashion

Provenance in Linked Data Integration

The open world of the (Semantic) Web is a global information space offering diverse materials of disparate qualities, and the opportunity to re-use, aggregate, and integrate these materials in novel ways. The advent of Linked Data brings the potential to expose data on the Web, creating new challenges for data consumers who want to integrate these data. One challenge is the ability, for users, to elicit the reliability and/or the accuracy of the data they come across. In this paper, we describe a light-weight provenance extension for the voiD vocabulary that allows data publishers to add provenance metadata to their datasets. These provenance metadata can be queried by consumers and used as contextual information for integration and inter-operation of information resources on the Semantic Web

Identifying communities of practice: analysing ontologies as networks to support community recognition

Communities of practice are seen as increasingly important for creating, sharing and applying organisational knowledge. Yet their informal nature makes them difficult to identify and manage. In this paper we set out ONTOCOPI, a system that applies ontology-based network analysis techniques to target the problem of identifying such communities

Social Machines

The term ‘social machine’ has recently been coined to refer to Web-based systems that support a variety of socially-relevant processes. Such systems (e.g., Wikipedia, Galaxy Zoo, Facebook, and reCAPTCHA) are progressively altering the way a broad array of social activities are performed, ranging from the way we communicate and transmit knowledge, establish romantic partnerships, generate ideas, produce goods and maintain friendships. They are also poised to deliver new kinds of intelligent processing capability by virtue of their ability to integrate the complementary contributions of both the human social environment and a global nexus of distributed computational resources. This chapter provides an overview of recent research into social machines. It examines what social machines are and discusses the kinds of social machines that currently exist. It also presents a range of issues that are the focus of current research attention within the Web Science community