Co-chairs and Members


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FAIR Implementation Profiles and Practice Group

Group updates

• Jan-Feb 2022: Making the ENVRIs “FIP for purpose” through FAIR Convergence
   ◦ Workshops archive:

• Fall 2020: GO FAIR / CODATA Pre-Symposium Convergence Workshops building 25 community FIPs
   ◦ Session
   ◦ Workshops archive
   ◦ FIPs as graphs (thanks to Kristina Hettne):
   ◦ Convergence Matrix:

• 2019: Early outputs of the original FIP Working Group
   ◦ Workshops archive:

The FAIR Implementation Profiles and Practice (FIPP) working group focuses on the role of FAIR Implementation Profiles (FIP) in the FDO space. FIPs impact the FDO development in 2 principal ways:

(1) FIPs provide a socio-technical approach for driving the explicit and systematic community agreements on the use of FAIR implementations including domain-relevant community standards (as per R1.3). Hence, FIPs can catalyze convergence both within and between disciplinary domains. In preparation for the 1st International FDO Conference from 26-28 October 2022, FIPP WG activities will leverage FIPs in gaining commitment to FDOs among a critical mass of circumscribed communities (ESFRIs, EU Programs, JRC, etc.) and broader stakeholders.

(2) Once a community of practice declares a FIP (in machine-readable format), the FIP itself becomes a type of FAIR metadata that describes the technical and semantic composition of FAIR digital objects that will be subsequently created by that community. The FIPP WG will explore how FIPs may be used to instruct computation agents to interpret, interoperate with, and perform operations on FDOs as they are constructed under given FIPs.

The FDO-FIP group is co-chaired by Erik Schultes and Barbara Magagna, and has active members from the original FIP working group. The group welcomes participation by experts in FAIR implementation, FDOs and convergence. For requests/comments send an email to

Background and links: 

  • Schultes E., Magagna B., Hettne K.M., Pergl R., Suchánek M., Kuhn T. (2020) Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence. In: Grossmann G., Ram S. (eds) Advances in Conceptual Modeling. ER 2020. Lecture Notes in Computer Science, vol 12584. Springer, Cham. [preprint]
  • H.P. Sustkova, K.M. Hettne, P. Wittenburg, A. Jacobsen, T. Kuhn, R. Pergl,… & E. Schultes. FAIR convergence matrix: Optimizing the reuse of existing FAIR-related resources. Data Intelligence 2(2020), 158–170. doi: 10.1162/dint_a_00038