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Notre Dame researchers lead CI Compass Topical Working Group on FAIR data principles for NSF Major Facilities, to host workshop in June

Scientific knowledge is advanced often one step at a time, and all research builds on what has been done before. With many repositories and platforms utilized by researchers, institutions, and laboratories throughout the national and the international science community, it is an ongoing challenge to ensure that information can be located, accessed, and properly credited. Having interoperable and reusable data will mean research and datasets are documented in ways that means others can not only recreate the science, but also that the materials can be utilized in machine learning and artificial intelligence (AI) initiatives as well. Being able to use datasets that are optimized for AI is an important consideration, and this can lead to faster processing and discovery in the process.…

Scientific knowledge is advanced often one step at a time, and all research builds on what has been done before. With many repositories and platforms utilized by researchers, institutions, and laboratories throughout the national and the international science community, it is an ongoing challenge to ensure that information can be located, accessed, and properly credited. Having interoperable and reusable data will mean research and datasets are documented in ways that means others can not only recreate the science, but also that the materials can be utilized in machine learning and artificial intelligence (AI) initiatives as well. Being able to use datasets that are optimized for AI is an important consideration, and this can lead to faster processing and discovery in the process.

These traits — findability, accessibility, interoperability, and reusability—are known as FAIR data practices. Creating data that is FAIR is an intentional decision of those who publish research and make datasets available.

At the end of the day, FAIR is about recognizing the value of the research data and taking efforts to be able to find and reuse it,” said Don Brower, CI Compass FAIR Data Expert and research assistant professor and computational scientist at the University of Notre Dame. "This is essential for extending results, and for running increasingly sophisticated computational simulations. It also recognizes that our analysis algorithms are improving and sometimes data can be reused in entirely different disciplines or contexts such as with the rise of large AI models.”

FAIR Data and the Year of Open Science

While FAIR data practices are not new, having been in discussion in the information and computer science communities since the late 1990s, the year 2023 has been designated as a "year of open science" with a broader push for adoption of the practices by federally funded research centers, including those funded by the National Science Foundation (NSF). These facilities were given an expedited direction release, titled "Ensuring Free, Immediate, and Equitable Access to Federally Funded Research" by Alondra Nelson, Deputy Assistant to the President and Deputy Director for Science and Society Performing the Duties of Director, from the White House Office of Science and Technology Policy (OSTP). It is commonly referred to as the “Nelson Memo,” which was released in August 2022.

The memo asks federally funded research centers to update their public access policies “as soon as possible, and no later than December 31, 2025,” to make research and supporting data available publicly without any embargo or cost on its release, have transparent procedures to preserve scientific and research integrity, and coordinate with OSTP to make sure that there is an “equitable delivery” of the results and data.

“A federal public access policy consistent with our values of equal opportunity must allow for broad and expeditious sharing of federally funded research–and must allow all Americans to benefit from the returns on our research and development investments without delay,” the memo says. “Upholding these core U.S. principles in our public access policy also strengthens our ability to be a critical leader and partner on issues of open science around the world.”

CI Compass takes steps to facilitate FAIR solutions

The CI Compass FAIR Topical Working Group (TWG) has been meeting since August 2022, when the memo was released. The TWG is led by members of CI Compass including Brower, Charles Vardeman, research assistant professor and computational scientist at the University of Notre Dame and CI Compass member, and Angela Murillo, assistant professor at the Luddy School of Informatics, Computing, and Engineering at Indiana University - Indianapolis and co-principal investigator for CI Compass, and is regularly attended by cyberinfrastructure practitioners from NSF Major Facilities (MFs) who are seeking discussions on ways to push FAIR data practices further in their own work. ORCID, a platform that provides a persistent identifier to researchers and publications, also has a representative regularly attending the meetings. In addition to their collaborative efforts with ORCID, CI Compass is also actively engaged with several FAIR data organizations including GoFAIR.us, the Research Data Alliance, Earth Science Information Partners, and CODATA, to further globalize and strengthen their data management practices. The goal of the FAIR Data TWG is to identify ways NSF MFs can work to implement these policies, and discuss new practices as they look ahead to how data will be used in the future. 

“Large research facilities are an integral part of global research infrastructure that have a profound impact on scientific research. Unfortunately, they face a variety of technical, social, and practical challenges to implementation of FAIR data and public access policies,” said David Butcher, research faculty, National High Magnetic Field Laboratory and CI Compass FAIR TWG member. “We look forward to bringing together personnel from large research facilities to discuss how we can address these challenges and transition to more modern, secure, and FAIR data management strategies.”

This June, the group will participate in the ACM/IEEE Joint Conference Digital Libraries 2023 (JCDL) by hosting a workshop titled “FAIR Data for Large Research Facilities.” The sessions will feature much of the findings of the working group since its inception. The workshop will be led by Don Brower and David Butcher. The workshop will include discussions of the findings from the CI Compass TWG.

The FAIR TWG is also led by Murillo and Vardeman. The TWG will also be discussing the findings of the survey that was distributed throughout spring 2023

Learn more about the ACM/IEEE Joint Conference Digital Libraries 2023 workshop here: https://ci-compass.org/news-and-events/events/2023/06/26/acm-ieee-joint-conference-on-digital-libraries/

Learn more about the FAIR Data Topical Working Group: https://ci-compass.org/news-and-events/news/working-group-formed-by-ci-compass-for-nsf-major-facilities-to-help-make-data-fair/


About CI Compass

CI Compass is funded by the NSF Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering under grant number 2127548. Its participating research institutions include the University of Southern California, Indiana University, Texas Tech University, the University of North Carolina at Chapel Hill, the University of Notre Dame, and the University of Utah.

To learn more about CI Compass, please visit ci-compass.org.

Contact:

Christina Clark, Research Communications Specialist

CI Compass / Notre Dame Research / University of Notre Dame

cclark26@nd.edu / 574.631.2665

ci-compass.org / @cicompass

Originally published by Christina Clark at ci-compass.org on June 08, 2023.

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