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Methods for intrinsic evaluation of links in the Web of Data

Methods for intrinsic evaluation of links in the Web of Data
Methods for intrinsic evaluation of links in the Web of Data
The current Web of Data contains a large amount of interlinked data. However, there is still a limited understanding about the quality of the links connecting entities of different and distributed data sets. Our goal is to provide a collection of indicators that help assess existing interlinking. In this paper, we present a framework for the intrinsic evaluation of RDF links, based on core principles of Web data integration and foundations of Information Retrieval.We measurethe extent to which links facilitate the discovery of an extended description of entities, and the discovery of other entities in other data sets. We also measure the use of different vocabularies. We analysed links extracted from a set of data sets from the Linked Data Crawl 2014 using these measures.
Sarasua, Cristina
8eda1bc4-faa8-46f2-9fab-782bf0f39994
Staab, Steffen
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Thimm, Matthias
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Sarasua, Cristina
8eda1bc4-faa8-46f2-9fab-782bf0f39994
Staab, Steffen
bf48d51b-bd11-4d58-8e1c-4e6e03b30c49
Thimm, Matthias
ec2f5286-032e-47c9-b169-811a2fa5d3f8

Sarasua, Cristina, Staab, Steffen and Thimm, Matthias (2017) Methods for intrinsic evaluation of links in the Web of Data. ESWC 2017, , Portoroz, Slovenia. 28 May - 01 Jun 2017. 15 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

The current Web of Data contains a large amount of interlinked data. However, there is still a limited understanding about the quality of the links connecting entities of different and distributed data sets. Our goal is to provide a collection of indicators that help assess existing interlinking. In this paper, we present a framework for the intrinsic evaluation of RDF links, based on core principles of Web data integration and foundations of Information Retrieval.We measurethe extent to which links facilitate the discovery of an extended description of entities, and the discovery of other entities in other data sets. We also measure the use of different vocabularies. We analysed links extracted from a set of data sets from the Linked Data Crawl 2014 using these measures.

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ESWC_2017_paper_192 - Author's Original
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More information

Accepted/In Press date: 22 February 2017
Venue - Dates: ESWC 2017, , Portoroz, Slovenia, 2017-05-28 - 2017-06-01
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 406415
URI: http://eprints.soton.ac.uk/id/eprint/406415
PURE UUID: 94614931-1840-4feb-aa20-ecb8b7aeb2fd
ORCID for Steffen Staab: ORCID iD orcid.org/0000-0002-0780-4154

Catalogue record

Date deposited: 10 Mar 2017 10:46
Last modified: 16 Mar 2024 04:22

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Contributors

Author: Cristina Sarasua
Author: Steffen Staab ORCID iD
Author: Matthias Thimm

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