Pistoia Alliance’s FAIR Maturity Assessment Tool
By Irene Yeh
June 17, 2025 | Findable, Accessible, Interoperable and Reusable (FAIR) principles continue to hold an important place in data management and access, artificial intelligence (AI) and machine learning (ML) development, and data sharing between organizations. But FAIR is also complex to implement due to the original FAIR guidelines not being explicit and difficult to understand or visualize for non-experts. As such, it can be a challenge to determine if an organization is ready to incorporate the principles into their strategies.
The FAIR community of experts with the Pistoia Alliance developed a self-assessment tool that can measure an organization’s FAIR maturity level. Though FAIR data maturity models and metrics already exist, the life sciences industry lacks a simple and standardized model that can be implemented at an organizational level. The FAIR Maturity Matrix is designed to help organizations benchmark and maximize their investment in FAIR principles at any maturity level. Whether they are getting started with their FAIR journey or trying to move to the next stage, the FAIR Maturity Matrix is designed to support the complex processes of FAIR data implementation in an efficient way. This project earned the Pistoia Alliance the Innovative Practices Award at the Bio-IT World Conference & Expo that took place in April of this year.
Measuring FAIR Maturity
Publicly launched in April 2024, the FAIR Maturity Matrix is a management tool for organizations at different stages of applying FAIR data principles to assess, qualify, and measure their progress.
“We noticed that there was a need to clarify what we’re talking about when we’re talking about FAIR data,” explained Giovanni Nisato, project manager of FAIR Implementation at the Pistoia Alliance and the team lead of the FAIR Maturity Matrix. One of the underlying issues was the lack of a benchmark and the need to compare notes across organizations. Furthermore, there needed to be a way to articulate and discuss digital and organizational transformations brought about by FAIR data implementation. “There are plenty of standards, but there is no FAIR data standard.”
One of the first elements to developing the Matrix (as the team nicknamed the tool) was determining what FAIR maturity would look like. The team boiled it down to seven dimensions to articulate the FAIR Maturity Matrix: FAIR data, FAIR leadership, FAIR strategy, FAIR roles, FAIR processes, FAIR knowledge, and FAIR tools and infrastructure. The dimensions are not ordered in importance. Instead, they all play a different and complementary role in the complex FAIR implementation journeys.
These dimensions were determined by “thematic analysis of conversations,” as Nisato described. The team originally had more than ten dimensions, but they decided that any amount greater than ten would overcomplicate an already complex process. So, they consolidated, clarified, re-labeled, and defined different dimensions until they reduced it to a set that was enough to encapsulate everything the Matrix would identify. Nisato noted that these dimensions could change in the future as the Matrix continues to improve and evolve.
Implementing the Matrix
Building upon these seven dimensions, the team created a working template. The next step was an arduous but “extremely enriching” process of going through the whole Matrix that required several guided conversations that took months. The resulting Matrix was then tested by other organizations, according to Nisato.
However, the Matrix isn’t “completely perfect and self-consistent” to FAIR principles in its present state. The tool helps with clarifying maturity levels and mapping out the next step, and “the same situation can be looked at with different perspectives.” Different perspectives can be a strength, but there is an underlying issue of different people—depending on their knowledge—possibly reaching different conclusions. The team tried to reduce this by giving descriptions that enable a substantiated assessment, and they aim to further improve on this.
Nonetheless, the FAIR Maturity Matrix proved that it provides a useful orientation framework or compass, as well as unlock data in siloes, utilize new insights to implement on AI/ML platforms, and encourage collaboration between companies to create new breakthroughs. The Matrix is a tool meant to support and help clear the murky first steps of FAIR implementation and maturity assessment.
Future Steps
Currently, organizations from different industries (including national research, funding bodies, pharmaceutical, and life sciences) are adopting the FAIR Maturity Matrix. Providers that support life science organizations are also adopting the Matrix for consultancy and technology purposes. As of now, version 1.1 is available, and the team is working on updating and improving some elements, says Nisato. “The version currently being developed is not going to be a revolution. It’s an improvement.”
With confirmation that the Matrix can be used for self-assessment, there are a few directions to go with this discovery, such as creating a process for trusted third-party assessments. Third-party assessments could be especially helpful to organizations that are at the beginning of their FAIR journey and do not have the knowledge, capability, or time to perform assessments.
“I think it’s going to unleash a different level of creativity. FAIR data is foundational for AI systems, and the Matrix is about helping organizations become better and creating and managing FAIR data.”