Engaging with Researchers and Raising Awareness of FAIR and Open Science through the FAIR+ Implementation Survey Tool (FAIRIST)
Christine R. Kirkpatrick, Kevin L. Coakley, Julie Christopher, Ines, Dutra

TL;DR
The paper introduces FAIRIST, a survey tool that helps researchers understand and implement FAIR and Open Science principles by integrating guidance into research proposals and providing tailored, just-in-time advice.
Contribution
FAIRIST is a novel survey tool that systematically incorporates FAIR and Open Science awareness into research proposals, addressing implementation challenges with AI and ML artifacts.
Findings
Researchers gain awareness of FAIR principles.
FAIRIST provides tailored, actionable guidance.
The tool integrates with research workflows and proposals.
Abstract
Six years after the seminal paper on FAIR was published, researchers still struggle to understand how to implement FAIR. For many researchers FAIR promises long-term benefits for near-term effort, requires skills not yet acquired, and is one more thing in a long list of unfunded mandates and onerous requirements on scientists. Even for those required to or who are convinced they must make time for FAIR research practices, the preference is for just-in-time advice properly sized to the scientific artifacts and process. Because of the generality of most FAIR implementation guidance, it is difficult for a researcher to adjust the advice to their situation. Technological advances, especially in the area of artificial intelligence (AI) and machine learning (ML), complicate FAIR adoption as researchers and data stewards ponder how to make software, workflows, and models FAIR and reproducible.…
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Taxonomy
TopicsResearch Data Management Practices · Scientific Computing and Data Management · Data Quality and Management
