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Digital publishing platforms and internet resources enable openness of access to scientific findings and data at scales never before realized. Unfortunately, researchers sometimes embrace lock-in systems for data generation and analysis out of necessity because meaningful alternatives do not exist. Scientific advances still take place when this occurs, but they become fragmented with discordant quality control, interoperability, reproducibility, and democratization of access. To maximize the value of these—often—publicly funded resources, disciplines are turning to FAIR Guiding Principles for data stewardship. FAIR (Findability, Accessibility, Interoperability, and Reuse) promotes the added value of widespread data sharing that is transparent, equitable, and inclusive. Here we present NoCTURN, an NSF-funded FAIR Open Science Research Coordination Network for computed tomography users. NoCTURN (the Non-clinical Computed Tomography Users Research Network) aims to address the fragmentation of tomography toolkits stemming from proprietary software, non-uniform metadata formats, and repeatability limits. In this presentation, we outline how we will achieve this aim together by 1) developing a community committed to information sharing; 2) coordinating data analysis, storage, and reporting requirements; 3) highlighting underrepresented voices in the field; 4) developing community standards inclusive of industry, research, education, and outreach stake-holders; and 5) modeling FAIR open science strategies for our colleagues and students. NoCTURN is recruiting undergraduates through established investigators from X-ray-, neutron-, and synchrotron-beam computed tomography communities—and we want to hear from you.
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Geoscience data publication: Practices and perspectives on enabling the FAIR guiding principles
Abstract Introduced in 2016, the FAIR Guiding Principles endeavour to significantly improve the process of today's data‐driven research. The Principles present a concise set of fundamental concepts that can facilitate the findability, accessibility, interoperability and reuse (FAIR) of digital research objects by both machines and human beings. The emergence of FAIR has initiated a flurry of activity within the broader data publication community, yet the principles are still not fully understood by many community stakeholders. This has led to challenges such as misinterpretation and co‐opted use, along with persistent gaps in current data publication culture, practices and infrastructure that need to be addressed to achieve a FAIR data end‐state. This paper presents an overview of the practices and perspectives related to the FAIR Principles within the Geosciences and offers discussion on the value of the principles in the larger context of what they are trying to achieve. The authors of this article recommend using the principles as a tool to bring awareness to the types of actions that can improve the practice of data publication to meet the needs of all data consumers. FAIR Guiding Principles should be interpreted as an aspirational guide to focus behaviours that lead towards a more FAIR data environment. The intentional discussions and incremental changes that bring us closer to these aspirations provide the best value to our community as we build the capacity that will support and facilitate new discovery of earth systems.
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- Award ID(s):
- 1924618
- PAR ID:
- 10368334
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Geoscience Data Journal
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2049-6060
- Page Range / eLocation ID:
- p. 177-186
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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