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The human face of the web of data: a cross-sectional study of labels

The human face of the web of data: a cross-sectional study of labels
The human face of the web of data: a cross-sectional study of labels
Labels in the web of data are the key element for humans to access the data. We introduce a framework to measure the coverage of information with labels. The framework is based on a set of metrics including completeness, unambiguity, multilinguality, labeled object usage, and monolingual islands. We apply this framework on seven diverse datasets, from the web of data, a collaborative knowledge base, open governmental and GLAM data. We gain an insight into the current state of labels and multilinguality on the web of data. Comparing a set of differently sourced datasets can help data publishers to understand what they can improve and what other ways of collecting and data can be adopted.
Linked Data, Web of Data, Labels, Semantic Web, multilinguality
Kaffee, Lucie-Aimée
8975c12f-9033-47ed-a2eb-b674b707c2ac
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67
Kaffee, Lucie-Aimée
8975c12f-9033-47ed-a2eb-b674b707c2ac
Simperl, Elena
40261ae4-c58c-48e4-b78b-5187b10e4f67

Kaffee, Lucie-Aimée and Simperl, Elena (2018) The human face of the web of data: a cross-sectional study of labels. SEMANTiCS 2018: 14th International Conference on Semantic Systems, , Vienna, Austria. 10 - 13 Sep 2018. 12 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

Labels in the web of data are the key element for humans to access the data. We introduce a framework to measure the coverage of information with labels. The framework is based on a set of metrics including completeness, unambiguity, multilinguality, labeled object usage, and monolingual islands. We apply this framework on seven diverse datasets, from the web of data, a collaborative knowledge base, open governmental and GLAM data. We gain an insight into the current state of labels and multilinguality on the web of data. Comparing a set of differently sourced datasets can help data publishers to understand what they can improve and what other ways of collecting and data can be adopted.

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Kaffee_The_Human_Face_of_the_Web_of_Data__a_cross_sectional_study_of_labels - Accepted Manuscript
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More information

Accepted/In Press date: 4 June 2018
Venue - Dates: SEMANTiCS 2018: 14th International Conference on Semantic Systems, , Vienna, Austria, 2018-09-10 - 2018-09-13
Keywords: Linked Data, Web of Data, Labels, Semantic Web, multilinguality

Identifiers

Local EPrints ID: 422848
URI: http://eprints.soton.ac.uk/id/eprint/422848
PURE UUID: f84543fc-bd75-4de4-86bd-af7a41d6a314
ORCID for Lucie-Aimée Kaffee: ORCID iD orcid.org/0000-0002-1514-8505
ORCID for Elena Simperl: ORCID iD orcid.org/0000-0003-1722-947X

Catalogue record

Date deposited: 07 Aug 2018 16:30
Last modified: 15 Mar 2024 21:09

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Contributors

Author: Lucie-Aimée Kaffee ORCID iD
Author: Elena Simperl ORCID iD

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