A Metrics-Driven Approach for Quality Assessment of Linked Open Data

The main objective of the Web of Data paradigm is to crystallize knowledge through the interlinking of already existing but dispersed data. The usefulness of the developed knowledge depends strongly on the quality of the published data. Researchers have observed many deficiencies with regard to the...

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Autores principales:	Behkamal,Behshid, Kahani,Mohsen, Bagheri,Ebrahim, Jeremic,Zoran
Lenguaje:	English
Publicado:	Universidad de Talca 2014
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762014000200006
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spelling	oai:scielo:S0718-187620140002000062018-10-12A Metrics-Driven Approach for Quality Assessment of Linked Open DataBehkamal,BehshidKahani,MohsenBagheri,EbrahimJeremic,Zoran The main objective of the Web of Data paradigm is to crystallize knowledge through the interlinking of already existing but dispersed data. The usefulness of the developed knowledge depends strongly on the quality of the published data. Researchers have observed many deficiencies with regard to the quality of Linked Open Data. The first step towards improving the quality of data released as a part of the Linked Open Data Cloud is to develop tools for measuring the quality of such data. To this end, the main objective of this paper is to propose and validate a set of metrics for evaluating the inherent quality characteristics of a dataset before it is released to the Linked Open Data Cloud. These inherent characteristics are semantic accuracy, syntactic accuracy, uniqueness, completeness and consistency. We follow the Goal-Question-Metric approach to propose various metrics for each of these five quality characteristics. We provide both theoretical validation and empirical observation of the behavior of the proposed metrics in this paper. The proposed set of metrics establishes a starting point for a systematic inherent quality analysis of open datasets.info:eu-repo/semantics/openAccessUniversidad de TalcaJournal of theoretical and applied electronic commerce research v.9 n.2 20142014-05-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762014000200006en10.4067/S0718-18762014000200006
institution	Scielo Chile
collection	Scielo Chile
language	English
description	The main objective of the Web of Data paradigm is to crystallize knowledge through the interlinking of already existing but dispersed data. The usefulness of the developed knowledge depends strongly on the quality of the published data. Researchers have observed many deficiencies with regard to the quality of Linked Open Data. The first step towards improving the quality of data released as a part of the Linked Open Data Cloud is to develop tools for measuring the quality of such data. To this end, the main objective of this paper is to propose and validate a set of metrics for evaluating the inherent quality characteristics of a dataset before it is released to the Linked Open Data Cloud. These inherent characteristics are semantic accuracy, syntactic accuracy, uniqueness, completeness and consistency. We follow the Goal-Question-Metric approach to propose various metrics for each of these five quality characteristics. We provide both theoretical validation and empirical observation of the behavior of the proposed metrics in this paper. The proposed set of metrics establishes a starting point for a systematic inherent quality analysis of open datasets.
author	Behkamal,Behshid Kahani,Mohsen Bagheri,Ebrahim Jeremic,Zoran
spellingShingle	Behkamal,Behshid Kahani,Mohsen Bagheri,Ebrahim Jeremic,Zoran A Metrics-Driven Approach for Quality Assessment of Linked Open Data
author_facet	Behkamal,Behshid Kahani,Mohsen Bagheri,Ebrahim Jeremic,Zoran
author_sort	Behkamal,Behshid
title	A Metrics-Driven Approach for Quality Assessment of Linked Open Data
title_short	A Metrics-Driven Approach for Quality Assessment of Linked Open Data
title_full	A Metrics-Driven Approach for Quality Assessment of Linked Open Data
title_fullStr	A Metrics-Driven Approach for Quality Assessment of Linked Open Data
title_full_unstemmed	A Metrics-Driven Approach for Quality Assessment of Linked Open Data
title_sort	metrics-driven approach for quality assessment of linked open data
publisher	Universidad de Talca
publishDate	2014
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-18762014000200006
work_keys_str_mv	AT behkamalbehshid ametricsdrivenapproachforqualityassessmentoflinkedopendata AT kahanimohsen ametricsdrivenapproachforqualityassessmentoflinkedopendata AT bagheriebrahim ametricsdrivenapproachforqualityassessmentoflinkedopendata AT jeremiczoran ametricsdrivenapproachforqualityassessmentoflinkedopendata AT behkamalbehshid metricsdrivenapproachforqualityassessmentoflinkedopendata AT kahanimohsen metricsdrivenapproachforqualityassessmentoflinkedopendata AT bagheriebrahim metricsdrivenapproachforqualityassessmentoflinkedopendata AT jeremiczoran metricsdrivenapproachforqualityassessmentoflinkedopendata
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A Metrics-Driven Approach for Quality Assessment of Linked Open Data

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