Dqv

Data quality vocabulary

The Data Quality Vocabulary provides a framework in which the quality of a dataset can be described, whether by the dataset publisher or by a broader community of users. It does not provide a formal, complete definition of quality, rather, it sets out a consistent means by which information can be provided such that a potential user of a dataset can make his/her own judgment about its fitness for purpose.

Editors

• Riccardo Albertoni, - Consiglio Nazionale delle Ricerche, Italy
• Antoine Isaac, University Amsterdam and Europeana, The Netherlands

Publications

• Latest published draft
• Editor's draft

Document Archive

• List of DQV implementations
• F2F São Paulo - Agenda Proposal DQV
• Data quality working space
• Data quality schedule
• DQV Editorial actions
• Translations for the classes and properties of DQV