Abstract
The Data Quality Vocabulary (DQV) provides a metadata model for expressing data quality. DQV was developed by the Data on the Web Best Practice (DWBP) Working Group of the World Wide Web Consortium (W3C) between 2013 and 2017. This paper aims at providing a deeper understanding of DQV. It introduces its key design principles, components, and the main discussion points that have been raised in the process of designing it. The paper compares DQV with previous quality documentation vocabularies and demonstrates the early uptake of DQV by collecting tools, papers, projects that have exploited and extended DQV.
| Original language | English |
|---|---|
| Pages (from-to) | 81-97 |
| Number of pages | 17 |
| Journal | Semantic Web |
| Volume | 12 |
| Issue number | 1 |
| Early online date | 19 Nov 2020 |
| DOIs | |
| Publication status | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 17 Partnerships for the Goals
Keywords
- Data quality
- DCAT
- metadata
- RDF vocabulary
- W3C
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