Introduction

The FAIR Data Principles dictate that data should be Findable, Accessible, Interoperable, and Reusable. By making data more FAIR, SRP grantees can accelerate the pace of research and uncover new insights.
The FAIR Data Principles dictate that data should be Findable, Accessible, Interoperable, and Reusable. By making data more FAIR, SRP grant recipients can accelerate the pace of research and uncover new insights.

In 2019, SRP facilitated science-driven collaborative projects to enhance data integration, interoperability, and reuse. To accomplish these goals, SRP encouraged the applicants to develop “use cases” demonstrating where data management and data sharing could advance the interoperability and reuse of diverse and complex SRP data streams and increase the FAIR-ness of data.

Collaborators pursued rigorous research questions and identified current limitations to inform data management efforts for the SRP in the future. Together, the 19 projects utilized more than 50 datasets from SRP-funded research centers and individual research projects, external collaborators, and state, local, and federal sources.

Teams began at different points along the spectrum of readiness for data interoperability.
Teams began at different points along the spectrum of readiness for data interoperability.

Teams starting at various stages along the spectrum of readiness for data interoperability worked together to set the groundwork to answer complex research environmental health questions that individual groups could not tackle alone.

Working closely with experts in data science, teams identified existing resources to advance FAIR-ness of SRP datasets and barriers to data sharing and interoperability.

For more details about each use case, including their innovative approaches to combining disparate datasets and creating user-friendly tools, the challenges teams experienced, and their recommendations to inform best practices for moving forward, please refer to the White Paper (2MB).