Rainford, P.F. orcid.org/0000-0002-0552-2209, Occhipinti, A. orcid.org/0000-0001-6075-1496, Wang, B. orcid.org/0000-0002-5815-6185 et al. (18 more authors) (2026) Knowledge preservation in the era of big science and AI: strategies for sustainable scientific research. Nature Communications, 17 (1). 4069. ISSN: 2041-1723
Abstract
Science is losing knowledge it cannot afford to lose. Negative results go unpublished, hard-won expertise walks out the door with departing researchers, and preservation efforts remain fragmented. The consequences are wasted resources, duplicated effort, and missed discoveries. In this perspective, we argue that the research community can act now by embracing alternative dissemination channels, improving documentation best practices, and building sustainable digital infrastructure. We envision moderated platforms for sharing null results and practical know-how, community-driven standards, and AI-powered tools that lower barriers to implementation. With coordinated effort, science can become more open, efficient, and resilient for future generations.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © The Author(s) 2026. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. |
| Keywords: | Computational biology and bioinformatics; Data publication and archiving; Molecular biology; Research data; Research management |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > School of Chemical, Materials and Biological Engineering The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences |
| Funding Information: | Funder Grant number UK RESEARCH AND INNOVATION MR/W00738X/1 |
| Date Deposited: | 13 Jul 2026 13:55 |
| Last Modified: | 13 Jul 2026 13:55 |
| Status: | Published |
| Publisher: | Springer Science and Business Media LLC |
| Refereed: | Yes |
| Identification Number: | 10.1038/s41467-026-72667-3 |
| Related URLs: | |
| Sustainable Development Goals: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:243057 |
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