The challenging FAIRisation route: how could assessment help?

We will run an informative and interactive session, aiming at introducing the audience to the latest assessment work, the challenges and opportunities, as well as the resources that work to help assisting the process of FAIRisation - FAIRisation includes prefairification, assessment before, during and after project implementation,  evaluation processes and support resources on the long term.

The scope of this session is to discuss the feasibility and methods for FAIR criteria adoption in all the fairisation steps related to evaluation processes, partially based on the results of the SHARC IG’s survey. This focus is complementary to the ongoing work in the FAIR data maturity model WG.

The following questions will be addressed:

• What is the place of FAIR assessment as regards other elements of scientific activities involved in data sharing?

• What are the steps required by the various actors in the fairisation preparation and how to choose processes and related tools?

• What is the role of repositories and standards providers (assessment for evaluation)? How can they ensure that their resources are visible and used by the community to enable FAIR data? How can FAIRsharing help? 

and specifically:

• Should all data be FAIRified

• Should FAIR assessment criteria be part of the scientific evaluation process (grant applications, call for projects, individual scientist evaluation of activities, recruitment and career steps, teams or laboratories evaluation, institution policies' assessment, other)

• Can criteria of FAIR assessment be considered as a part of data quality assessment

• Which stakeholders need to be involved to prepare researchers for making their data FAIR ? Which aspect of FAIR will each stakeholder cover? 

• How can researchers best be prepared in the pre-FAIRification stage for making their data FAIR? Is this a once off or will there be aspects that will need to be revisited throughout the research lifecycle?

• There is no agreed naming convention for classifying standards for reporting and sharing data, metadata and other digital objects. Do you think we need such common classification?

• How can a repository increase it’s visibility to researchers and policymakers?

• To measure the use and adoption of standards, showing which repositories implement them is essential, but how else can the adoption of standards be measured?