License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GISCIENCE.2018.50
URN: urn:nbn:de:0030-drops-93786
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2018/9378/
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Mocnik, Franz-Benjamin

Linked Open Data Vocabularies for Semantically Annotated Repositories of Data Quality Measures (Short Paper)

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Abstract

The fitness for purpose concerns many different aspects of data quality. These aspects are usually assessed independently by different data quality measures. However, for the assessment of the fitness for purpose, a holistic understanding of these aspects is needed. In this paper we discuss two Linked Open Data vocabularies for formally describing measures and their relations. These vocabularies can be used to semantically annotate repositories of data quality measures, which accordingly adhere to common standards even if being distributed on multiple servers. This allows for a better understanding of how data quality measures relate and mutually constrain. As a result, it becomes possible to improve intrinsic data quality measures by evaluating their effectivity and by combining them.

BibTeX - Entry

@InProceedings{mocnik:LIPIcs:2018:9378,
  author =	{Franz-Benjamin Mocnik},
  title =	{{Linked Open Data Vocabularies for Semantically Annotated Repositories of Data Quality Measures (Short Paper)}},
  booktitle =	{10th International Conference on Geographic Information  Science (GIScience 2018)},
  pages =	{50:1--50:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Stephan Winter and Amy Griffin and Monika Sester},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9378},
  URN =		{urn:nbn:de:0030-drops-93786},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.50},
  annote =	{Keywords: data quality, measure, semantics, Linked Open Data (LOD), vocabulary, repository, reproducibility, OpenStreetMap (OSM)}
}

Keywords: data quality, measure, semantics, Linked Open Data (LOD), vocabulary, repository, reproducibility, OpenStreetMap (OSM)
Collection: 10th International Conference on Geographic Information Science (GIScience 2018)
Issue Date: 2018
Date of publication: 02.08.2018
Supplementary Material: http://purl.org/data-quality, http://purl.org/osm-data-quality

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