Discover the data.europa academy training session on data and metadata quality
This webinar provides tips and tricks on how to ensure good quality data and metadata
Learn more about data and metadata quality by watching the recording of the latest data.europa academy training session! In the session, Benjamin Dittwald and Lina Bruns from Fraunhofer FOKUS, a technical partner of the data.europa.eu, showcase:
- Data quality dimensions: Findability, Accessibility, Interoperability, and Reusability, also known as the FAIR principles
- The data preparation process
- The difference and connection between data quality and metadata quality
- Metadata quality standards such as DCAT-AP and the data.europa.eu Metadata Quality Assessment
- The data.europa.eu data quality guidelines
The session also highlights that data quality is all about the fitness of data. As Lina Bruns mentioned: “Data quality is a construct. Data quality is quite subjective, and it depends on what the data user wants to do with the data.”
Curious to learn more? You can find the recording and the slides on the data.europa academy.
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