Version: 1.0 Date: 2024-03 04-19
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FAIR Maturity Matrix V1.0 © 2024 by Pistoia Alliance is licensed under. CC BY 4.0
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"Reusable" refers to the suitability of data for use in different contexts and by different stakeholders, both humans and machines. Reusability involves providing clear and comprehensive documentation, including metadata, about the data's content, structure, and usage permissions. This documentation should be easily understandable and accessible to facilitate the effective reuse of the data by others. Additionally, data should be formatted in a standardized and interoperable manner, allowing it to be integrated with other datasets and analyzed using various tools and methods. By making data reusable, researchers can efficiently leverage existing datasets for new analyses and investigations, accelerating scientific progress and innovation. Moreover, clear usage licenses and permissions should accompany the data to specify how it can be reused, ensuring legal and ethical compliance.
Who worked on this model? FAIR implementation project, Best Practice Working group
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In February 2023, the Best Practice Working group Best Practices of the Pistoia Alliance’s FAIR implementation project started creating a cross-sector, organizational-level maturity model for FAIR implementation stages in the life sciences. This model is intended to assist decision makers in evaluating the stage of a given organization (or department) in terms of FAIR maturity, assess the options to achieve higher maturity levels and identify relevant resources that may be required to do so.
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As self-consistent and actionable as possible, the interpretation of the content should be in the context of lower and higher maturity levels and different dimensions. The structure of the first model is a matrix. We see each matrix element in relation not only to its nearest neighbors for the “maturity axis” but with all the elements in the same level, or the “dimensions axis”. That would, in turn, indicate concrete directions for improvement.
As much as possible, we use commonly understood and ideally referenced terminology. We provide examples of relevant practices, cases or implementations as much as possible. Where possible, we use references to known definitions.
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