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Such a community is fruitful to exchange knowledge and learn from each other, and to make improve the interoperability of data within the domain by making joint decisions on FAIRification: writing FIPs, decide on controlled vocabularies and metadata schemas.
The role of a Data Steward
FAIR Data stewardship is a relatively new profession that emerged to support researchers in data handling before, during and after a research project. Data stewards are trained to make data as FAIR (Findable, Accessible, Interoperable, Reusable) as possible and to advise researchers on data sharing. With the support of data stewards, data gain more value, as they become reusable and available for future research after a research project ends. To get a general idea on the backgrounds and experiences of professionals working with FAIR in the health domain, visit the Health-RI Data champion portfolio.
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Joining and forming communities is an important tool to strengthen the data steward profession by sharing experience and knowledge.
How to
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join an existing community
There are already active communities out there, some specifically for the profession of data steward and for a range of health-related domains. In the next sections we give you some examples of communities you could join.
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Domain specific communities
In health research and innovation, many researchers and data professionals from
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specific domains
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come together to share their experiences. Here are a few examples:
Also, just ask around, your colleagues will possibly know of communities related to your research domain.
How to
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build a new or improve an existing community
For researchers who receive a research grant, it is recommended to join or start a project specific community involving both researchers with knowledge on the relevant research domain, and data stewards with FAIR data-expertise. An example of such a community is the “ZonMw COVID programme”: a data champions group consisting of the project’s PIs and data stewards. This community was facilitated by the Data Stewards Interest Group (DSIG) and GO FAIR Foundation. The community collaborated during the programme, shared experiences, learned from each other and used their joint knowledge to produce and use FAIR COVID data by bringing together their project metadata with domain specific machine actionable metadata schemes, exposed in the Health-RI portal.
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