FAIR Maturity Matrix: Dimensions (rows)

The working group identified the  7 dimensions to articulate the FAIR maturity model. The dimensions are not hierarchical; each provides a different and complementary perspective on a given facet of a complex environment.

These different dimensions are the “rows” of the FAIR Maturity Matrix.

Combining all these factors is required to describe a given maturity level. It is also possible for organizations to reach various levels at a given point depending on the granularity (e.g. ecosystem/ enterprise/sector/department, etc.) considered. It is also possible for maturity to be not completely in sync for all dimensions. While FAIR implementation journeys may be similar, they are very context-dependent: the various dimensions intend to provide a broad frame to describe the situation accurately. 

FAIR data

This dimension concerns metadata, data, and data products. Several frameworks to evaluate the maturity of FAIR data exist publicly and in private organizational environments. The intention of this dimension is to provide a qualitative pragmatic indication, not to replace any of the existing models.  Especially at the initial levels, it should help identify the FAIR data principles in focus when starting a FAIR data implementation journey. This dimension closely connects to FAIR tools, infrastructures, processes, and roles.

(Back to the FAIR Matrix).

FAIR leadership

This dimension deals with types and leadership levels required to implement FAIR principles in a life science organization. Ultimately, leadership "owns" the vision of FAIR implementation, or the “why”.  Leadership roles are also necessary to ensure that strategies can be defined, enabled, implemented, and executed. Leadership ensures the resources (financial, time, priority) are set and available. Ultimately, leadership, at various levels in and outside the boundaries of the organizations, is accountable for implementing FAIR data principles. This requires a sufficiently deep level of understanding of the FAIR principles, of the costs (time, financial, opportunity) associated with data practices that are not FAIR and the skills needed to implement FAIR data principles.

(Back to the FAIR Matrix).

FAIR strategy       

Strategies are frameworks for making decisions related to FAIR implementation, from business case to capability-building to running operations. After setting the "why" of FAIR implementation journeys and what "will success look like,” "how and with which priorities will the organization evolve given the current status?” This dimension is also concerned with deciding what not to do (e.g., only some data may need to be FAIR, “FAIR Enough”), identifying metrics, organizational sectors (beyond R&D) involved and the cultural change required.

(Back to the FAIR Matrix).

FAIR roles

We address the roles required in an organization to implement FAIR principles in this dimension. What are the jobs to do? Who would ensure that happens? Who are the people responsible for FAIR implementation? These roles will ensure project execution to build capabilities and operational roles maintaining FAIR processes.

(Back to the FAIR Matrix).

FAIR  processes

FAIR data principles implementation requires underlying processes connecting the necessary metadata, data, tools, roles and knowledge. Some of these processes may be implicit in the early stages of FAIR data implementation. Still, they will become more explicit and so ubiquitous that they will become transparent once we achieve the highest maturity levels.

(Back to the FAIR Matrix).

FAIR knowledge       

The FAIR Knowledge dimension concerns the factual, conceptual, procedural  knowledge required for FAIR implementation at the various stages. Knowledge is often associated with human expert roles and connects with the “FAIR roles” dimension. 

(Back to the FAIR Matrix).

FAIR tools and infrastructures

This dimension concerns the essential information technology tools and infrastructures needed to implement FAIR data principles. It is closely related to the “FAIR data” dimension of the maturity model. The close relationship between FAIR implementation and semantic web technologies underscores the significance of the tools required to implement the FAIR principles. Beyond these aspects, additional frameworks that can enhance the implementation of FAIR data principles, broadening the scope of considerations for a comprehensive approach, are considered.

The FAIR tools and infrastructure dimension has an indicator for each element of FAIR. This indicator helps show the contribution the tool or infrastructure makes to the maturity level:

Findability The tool or infrastructure component contributes, enhances or enriches Findability.

Accessibility The tool or infrastructure component contributes, enhances or enriches Accessibility.

Reusability The tool or infrastructure component contributes, enhances or enriches Reusability.

Interoperability The tool or infrastructure component contributes, enhances or enriches Interoperability.

(Back to the FAIR Matrix).