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.
Introducing the Data Quality Vocabulary (DQV)
Riccardo Albertoni;
2021
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.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
