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SPORTAL: Profiling the Content of Public SPARQL Endpoints


Ali Hasnain, Qaiser Mehmood, Syeda Sana e Zainab, Aidan Hogan

Publication Type: 
Refereed Review Article
Access to hundreds of knowledge bases has been made available on the Web through public SPARQL endpoints. Unfortunately, few endpoints publish descriptions of their content (e.g., using VoID). It is thus unclear how agents can learn about the content of a given SPARQL endpoint or, relatedly, find SPARQL endpoints with content relevant to their needs. In this paper, the authors investigate the feasibility of a system that gathers information about public SPARQL endpoints by querying them directly about their own content. With the advent of SPARQL 1.1 and features such as aggregates, it is now possible to specify queries whose results would form a detailed profile of the content of the endpoint, comparable with a large subset of VoID. In theory it would thus be feasible to build a rich centralised catalogue describing the content indexed by individual endpoints by issuing them SPARQL (1.1) queries; this catalogue could then be searched and queried by agents looking for endpoints with content they are interested in. In practice, however, the coverage of the catalogue is bounded by the limitations of public endpoints themselves: some may not support SPARQL 1.1, some may return partial responses, some may throw exceptions for expensive aggregate queries, etc. The authors' goal in this paper is thus twofold: (i) using VoID as a bar, to empirically investigate the extent to which public endpoints can describe their own content, and (ii) to build and analyse the capabilities of a best-effort online catalogue of current endpoints based on the (partial) results collected.
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International Journal on Semantic Web and Information Systems (IJSWIS)
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