Discover the data.europa academy training session on data and metadata
quality
Learn more about data and metadata quality by watching the recording
of the latest data.europa academy training session!
[https://data.europa.eu/en/academy/improving-your-data-publishing-approach]
In the session, Benjamin Dittwald and Lina Bruns from Fraunhofer FOKUS
[https://www.fokus.fraunhofer.de/en], a technical partner of the
data.europa.eu, showcase:

 	* Data quality dimensions: Findability, Accessibility,
Interoperability, and Reusability, also known as the FAIR principles
[https://www.go-fair.org/fair-principles/]
 	* The data preparation process
 	* The difference and connection between data quality and metadata
quality
 	* Metadata quality standards such as DCAT-AP
[https://joinup.ec.europa.eu/collection/semantic-interoperability-community-semic/solution/dcat-application-profile-data-portals-europe]
and the data.europa.eu Metadata Quality Assessment
[https://data.europa.eu/mqa/?locale=en.]
 	* The data.europa.eu data quality guidelines
[https://op.europa.eu/en/publication-detail/-/publication/023ce8e4-50c8-11ec-91ac-01aa75ed71a1]


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
[https://www.youtube.com/watch?v=PcyJX8xbyik] and the slides
[https://data.europa.eu/sites/default/files/course/data.europa.eu_training%20session_data%20and%20metadata%20quality.pdf] on
the data.europa academy [https://data.europa.eu/en/academy].

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Publication Date/Time
2022-03-11T09:00:00+00:00
This webinar provides tips and tricks on how to ensure good quality
data and metadata