Eager: CI paos: fair samples: exploring research and sample data management best practices in place-based research

This National Science Foundation (NSF) Geosciences program (CFDA 47.050) Project Grant award, titled "EAGER: CI PAOS: FAIR SAMPLES: Exploring Research and Sample Data Management Best Practices in Place-Based Research," will provide $130,000 in funding from August 1, 2024 to July 31, 2026 to The Regents of the University of California.

The project aims to refine the management of physical research samples at field stations, integrating FAIR (Findable, Accessible, Interoperable, and Reusable) principles to improve data integrity and integration. Key objectives include enhancing a persistent identifier (PID)-enabled sample management system, developing flexible sample relationship modeling, and providing guidelines for implementing FAIR-compliant sample workflows. A sub-award to the RSPACE team will support technology platform development, relationship modeling strategies, and FAIR best practices for sample management.

This award reflects NSF's mission to expand fundamental knowledge and understanding of the integrated Earth system through basic research in atmospheric, earth, and ocean sciences. The project's focus on improving data management practices at field stations is expected to have a significant impact on advancing place-based research and innovation.

Abstract

Field stations represent crucial sites where the application of fair (findable, accessible, interoperable, and reusable) principles?concepts designed to improve metadata preparation and ensure that research data is both discoverable and interoperable?can significantly impact local communities by advancing research and innovation. These stations are essential for collecting primary data across various disciplines and present a unique opportunity to enhance community development through improved research practices. One of the primary challenges in field-based research is the efficient management of physical samples, which is vital for data integrity and the integration of different data types. This project has identified significant inefficiencies in how samples are cataloged and managed at these stations, affecting data retention and quality, as well as the integration of sample data with experimental data in adherence to fair principles. A key challenge in field-based research is the efficient management of physical samples, crucial for data integrity and the integration of various data types. The fair samples project aims to refine the process of managing these samples from the ground up, emphasizing the integration of fair principles into the existing workflows of researchers. The project will explore how a persistent identifier (PID)-enabled sample management system can interoperate with other research tools to streamline the entire sample lifecycle. This award by the office of advanced cyberinfrastructure within the directorate for computer and information science and engineering is jointly supported by the division of research, innovation, synergies, and education within the directorate for geosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are planned for this award.