GREI Data Repository AI Taxonomy
This work provides a framework for data repository managers to systematically incorporate AI, but it is incremental as it builds on existing repository concepts without introducing new AI methods.
The paper tackled the problem of integrating AI into data repository management by developing a taxonomy that categorizes repository roles into stages such as acquisition and validation, resulting in a structured framework for implementation.
The Generalist Repository Ecosystem Initiative (GREI), funded by the NIH, developed an AI taxonomy tailored to data repository roles to guide AI integration across repository management. It categorizes the roles into stages, including acquisition, validation, organization, enhancement, analysis, sharing, and user support, providing a structured framework for implementing AI in repository workflows.