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Abstract. RKB Explorer is a Semantic Web application that is able to present unified views of a significant number of heterogeneous data sources. We have developed an underlying information infrastructure which is mediated by ontologies and consists of many independent triplestores, each publicly available through both SPARQL endpoints and resolvable URIs. To realise this synergy of disparate information sources, we have deployed tools to identify co-referent URIs, and devised an architecture to allow the information to be represented and used. This paper provides a brief overview of the system including the underlying infrastructure, and a number of associated tools for both knowledge acquisition and publishing.

Abstract-The mission of the Advanced Knowledge Technologies (AKT) project is to investigate how to operationalise the knowledge management mantra of "getting the right content to the right place at the right time and in the right form." A significant result of the first three years of this six year project is CS AKTive Space (CAS), a Semantic Web application that won the 2003 Semantic Web Challenge. The challenge criteria included having to use geographically distributed, real world data that would have to be used in a context distinct from which that original data had been designed to serve. CAS is an application that, in meeting this criteria, seeks to provide the experience of an integrated information overview that allows a user to determine quickly who is doing what where in computer science research in the UK. In developing the application we have engaged a number of core Semantic Web challenges: content acquisition, ontology development to mediate heterogeneous data sources, scalable RDF storage and query facilities, and semantically directed interaction design. From our work on CAS we have begun to look at how the approaches for CAS can be generalised for the deployment of AKTive Space applications, dynamically generated from an ontology and set of services.

There has been lately an increased activity of publishing structured data in RDF due to the activity of the Linked Data community 1 . The presence on the Web of such a huge information cloud, ranging from academic to geographic to gene related information, 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 frameworks, implies a reasoning step over huge amounts of data, that is often hard to implement and rarely scales on Web dimensions. This paper presents an algorithm for achieving RDF data mediation based on SPARQL query rewriting. The approach is based on the encoding of rewriting rules for RDF patterns that constitute part of the structure of a SPARQL query.

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