Arrow Left Data stewardship handbook (HANDS)

Definitions of data stewardship

Data stewardship involves all activities required to ensure that digital research data are findable, accessible, interoperable, and reusable (FAIR) in the long term. This includes data management, archiving, and reuse by third parties. It is an ongoing learning process that is continually refined and tailored to your specific research project.

Adequate data stewardship ensures that:

  • you have adequate storage space, back up, support staff time;
  • your data is well described with reference- & meta data;
  • your data will be free from versioning errors and gaps in documentation;
  • possibly, your data can be used for healthcare purposes (medical research data);
  • your data is FAIR and can be shared with others, for scientific research, commercial development, or validation;
  • you meet legal and ethical requirements, including privacy of study subjects;
  • your data is backed up and safe from sudden loss or corruption;
  • you will get the best possible value from your research data investments;
  • you are able to share your final data set publicly;
  • your data will remain accessible and comprehensible in the future.

In 2019 a report has been written as part of the ZonMw funded project “Towards a community-endorsed data steward profession description for life science research”. This report defined, for the first time, the data steward function for the life sciences

domain at the level of detail necessary to implement the function profiles in the research institutes and to appoint data stewards. A short summary of the report can be found at the website of DTL.

The overview of existing training material and the outline for a new training give a basis for formalizing data steward education to further professionalise the data steward function. This will increase the capacity and quality of data stewards in the institutes and the life sciences domain in general.

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