Deriving human-readable labels from SPARQL queries
Deriving human-readable labels from SPARQL queries
Over 80% of entities on the Semantic Web lack a human-readable label. This hampers the ability of any tool that uses linked data to offer a meaningful interface to human users. We argue that methods for deriving human-readable labels are essential in order to allow the usage of the Web of Data. In this paper we explore, implement, and evaluate a method for deriving human-readable labels based on the variable names used in a large corpus of SPARQL queries that we built from a set of log files. We analyze the structure of the SPARQL graph patterns and offer a classification scheme for graph patterns. Based on this classification, we identify graph patterns that allow us to derive useful labels. We also provide an overview over the current usage of SPARQL in the newly built corpus.
978-1-4503-0621-8
126-133
Ell, B.
74a87aef-b03f-42d9-89be-4d49fafcf86f
Vrandecic, D.
2642fe14-9606-4ee3-8616-67f30849f3b3
Simperl, E.
40261ae4-c58c-48e4-b78b-5187b10e4f67
September 2011
Ell, B.
74a87aef-b03f-42d9-89be-4d49fafcf86f
Vrandecic, D.
2642fe14-9606-4ee3-8616-67f30849f3b3
Simperl, E.
40261ae4-c58c-48e4-b78b-5187b10e4f67
Ell, B., Vrandecic, D. and Simperl, E.
(2011)
Deriving human-readable labels from SPARQL queries.
7th International Conference on Semantic Systems (I-SEMANTICS2011), Graz, Austria.
07 - 09 Sep 2011.
.
(doi:10.1145/2063518.2063535).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Over 80% of entities on the Semantic Web lack a human-readable label. This hampers the ability of any tool that uses linked data to offer a meaningful interface to human users. We argue that methods for deriving human-readable labels are essential in order to allow the usage of the Web of Data. In this paper we explore, implement, and evaluate a method for deriving human-readable labels based on the variable names used in a large corpus of SPARQL queries that we built from a set of log files. We analyze the structure of the SPARQL graph patterns and offer a classification scheme for graph patterns. Based on this classification, we identify graph patterns that allow us to derive useful labels. We also provide an overview over the current usage of SPARQL in the newly built corpus.
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Published date: September 2011
Venue - Dates:
7th International Conference on Semantic Systems (I-SEMANTICS2011), Graz, Austria, 2011-09-07 - 2011-09-09
Organisations:
Web & Internet Science
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Local EPrints ID: 351613
URI: http://eprints.soton.ac.uk/id/eprint/351613
ISBN: 978-1-4503-0621-8
PURE UUID: db74a777-79ad-4273-88a8-f2a6f8d9dd81
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Date deposited: 29 Apr 2013 14:16
Last modified: 14 Mar 2024 13:41
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Author:
B. Ell
Author:
D. Vrandecic
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