Institutional Data Evaluation and Assessment (IDEA) Maturity Model

The Institutional Data Evaluation and Assessment (IDEA) Maturity Model is a framework designed to help research institutions assess their current capacity and practices for evaluating research data contributions and to identify opportunities for growth. It offers a structured, flexible approach for reflection and strategic planning, supporting institutions, libraries, and other stakeholders working to recognize research data as a first-class research output.

The IDEA model focuses on the institutional dimensions most relevant to evaluating data contributions: cultural norms, policies and processes, and activities related to reporting, rewarding, and recognizing data as part of researcher assessment. While this model is centered on evaluation, it assumes that basic data sharing and reuse infrastructure is already in place, aligned with community norms and policies such as FAIR, CARE, or funder requirements. It is designed to complement, rather than replace, other maturity models that focus on organizational readiness for data sharing and stewardship.

The IDEA model describes four distinct phases of institutional maturity:

• Initial: Capacity is limited or ad hoc, with few supporting resources, services, or cultural expectations

• Emerging: Minimal and often compliance-driven capacity has begun to take shape

• Established: Evaluation practices are formalized but may be uneven across units or disciplines

• Optimizing: Capacity is embedded, regularly refined, and continuously improving

Engaging with the IDEA model is intended as a learning exercise, not a pass or fail evaluation. Institutions may use the model through workshops, focus groups, or individual reflection. We recommend involving a diverse group of stakeholders including researchers, librarians, data managers, and administrators to ensure a well-rounded assessment. Documenting and revisiting the process over time can support sustained progress and adaptation to the evolving landscape of research data.

While we encourage sharing insights from this self-assessment, the IDEA model is not a benchmarking tool. It is not designed to compare institutions, but rather to help each institution reflect on its unique context, set meaningful goals, and track its progress. By using the IDEA model, institutions can make tangible strides toward more robust, fair, and transparent evaluation of data contributions, ultimately supporting a more inclusive and open research ecosystem.