On the Quality of Vocabularies for Linked Dataset Papers Published in the Semantic Web Journal

Tracking #: 1794-3007

Authors: 
Stella Sam
Pascal Hitzler
Krzysztof Janowicz

Responsible editor: 
Pascal Hitzler

Submission type: 
Editorial
Abstract: 
In the last few years a significant number of publications have laid out possible quality measures and corresponding algorithms for linked data quality assessment. However the final verdict is still outstanding regarding the question what dimensions or measures are in fact the most relevant for assessing Linked Data quality. One of the aspects which has so far not received sufficient attention, is the question of relevance of a quality schema or vocabulary for the quality of a linked dataset. Therefore, in this work, we will look at all linked dataset papers published in the Semantic Web journal and assess them from the perspective of the 5-star linked data vocabulary principles which we laid out in a previous editorial. This serves both as a partial assessment of the quality of linked dataset papers in the Semantic Web journal, and as assessment of the 5-star principles and their applicability in practice.
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Tags: 
Reviewed

Decision/Status: 
Accept

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