International Journal of Information and Communication Technology Research, Volume (8), No (3), Year (2016-9) , Pages (1-20)

Title : ( A metric Suite for Systematic Quality Assessment of Linked Open Data )

Authors: Behshid Behkamal , mohsen kahani , Ebrahim Bagheri , Majid Sazvar ,

Citation: BibTeX | EndNote

The vision of the Linked Open Data (LOD) initiative is to provide a distributed model for publishing and meaningfully interlinking open data. The realization of this goal depends strongly on the quality of the data that is published as a part of the LOD. This paper focuses on the systematic quality assessment of datasets prior to publication on the LOD cloud. To this end, we identify important quality deficiencies that need to be avoided and/or resolved prior to the publication of a dataset. We then propose a set of metrics to measure these quality deficiencies in a dataset. This way, we enable the assessment and identification of undesirable quality characteristics of a dataset through our proposed metrics. This will help publishers to filter out low-quality data based on the quality assessment results, which in turn enables data consumers to make better and more informed decisions when using the open datasets.

Keywords

, Metrics, RDF Datasets, Systematic Assessment, Quality Deficiencies, Linked Open
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@article{paperid:1060189,
author = {Behkamal, Behshid and Kahani, Mohsen and Ebrahim Bagheri and Sazvar, Majid},
title = {A metric Suite for Systematic Quality Assessment of Linked Open Data},
journal = {International Journal of Information and Communication Technology Research},
year = {2016},
volume = {8},
number = {3},
month = {September},
issn = {2251-6107},
pages = {1--20},
numpages = {19},
keywords = {Metrics; RDF Datasets; Systematic Assessment; Quality Deficiencies; Linked Open Data},
}

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%0 Journal Article
%T A metric Suite for Systematic Quality Assessment of Linked Open Data
%A Behkamal, Behshid
%A Kahani, Mohsen
%A Ebrahim Bagheri
%A Sazvar, Majid
%J International Journal of Information and Communication Technology Research
%@ 2251-6107
%D 2016

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