Linked Open Data vocabularies for semantically annotated repositories of data quality measures

F._B. Mocnik*

*Corresponding author for this work

Research output: Contribution to conferencePaperAcademicpeer-review

2 Citations (Scopus)
3 Downloads (Pure)

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.
Original languageEnglish
Pages1-7
Number of pages7
DOIs
Publication statusPublished - 28 Aug 2018
Externally publishedYes
Event10th International Conference on Geographic Information Science, GIScience 2018 - RMIT University, Melbourne, Australia
Duration: 28 Aug 201831 Aug 2018
Conference number: 10

Conference

Conference10th International Conference on Geographic Information Science, GIScience 2018
Abbreviated titleGIScience 2018
CountryAustralia
CityMelbourne
Period28/08/1831/08/18

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