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Linked data querying through FCA-based schema indexing

Linked data querying through FCA-based schema indexing
Linked data querying through FCA-based schema indexing
The effciency of SPARQL query evaluation against Linked Open Data may benefit from schema-based indexing. However, many data items come with incomplete schema information or lack schema descriptions entirely. In this position paper, we outline an approach to an indexing of linked data graphs based on schemata induced through Formal Concept Analysis. We show how to map queries onto RDF graphs based on such derived schema information. We sketch next steps for realizing and optimizing the suggested approach.
63-68
Brosius, Dominik
9bec443c-da9a-43e3-8aa1-dbb587b56762
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Brosius, Dominik
9bec443c-da9a-43e3-8aa1-dbb587b56762
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49

Brosius, Dominik and Staab, Steffen (2016) Linked data querying through FCA-based schema indexing. Proceedings of the 5th International Workshop "What can FCA do for Artificial Intelligence"? co-located with the European Conference on Artificial Intelligence, (FCA4AI@ECAI 2016), Netherlands. 30 Aug 2016. pp. 63-68 .

Record type: Conference or Workshop Item (Paper)

Abstract

The effciency of SPARQL query evaluation against Linked Open Data may benefit from schema-based indexing. However, many data items come with incomplete schema information or lack schema descriptions entirely. In this position paper, we outline an approach to an indexing of linked data graphs based on schemata induced through Formal Concept Analysis. We show how to map queries onto RDF graphs based on such derived schema information. We sketch next steps for realizing and optimizing the suggested approach.

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More information

Accepted/In Press date: 7 July 2016
Published date: 30 August 2016
Venue - Dates: Proceedings of the 5th International Workshop "What can FCA do for Artificial Intelligence"? co-located with the European Conference on Artificial Intelligence, (FCA4AI@ECAI 2016), Netherlands, 2016-08-30 - 2016-08-30
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 404015
URI: https://eprints.soton.ac.uk/id/eprint/404015
PURE UUID: 6cfa44da-3762-4a10-8892-8857110416fb
ORCID for Steffen Staab: ORCID iD orcid.org/0000-0002-0780-4154

Catalogue record

Date deposited: 19 Dec 2016 16:33
Last modified: 19 Jul 2019 00:35

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