Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science
In this paper, we explore the crucial role and challenges of computational reproducibility in geosciences, drawing insights from the Climate Informatics Reproducibility Challenge (CICR) in 2023. The competition aimed at (1) identifying common hurdles to reproduce computational climate science; and (...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2025-01-01
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| Series: | Environmental Data Science |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S2634460224000359/type/journal_article |
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| author | Alejandro Coca-Castro Anne Fouilloux Ricardo Barros Lourenço Andrew McDonald Yuhan Rao J. Scott Hosking |
| author_facet | Alejandro Coca-Castro Anne Fouilloux Ricardo Barros Lourenço Andrew McDonald Yuhan Rao J. Scott Hosking |
| author_sort | Alejandro Coca-Castro |
| collection | DOAJ |
| description | In this paper, we explore the crucial role and challenges of computational reproducibility in geosciences, drawing insights from the Climate Informatics Reproducibility Challenge (CICR) in 2023. The competition aimed at (1) identifying common hurdles to reproduce computational climate science; and (2) creating interactive reproducible publications for selected papers of the Environmental Data Science journal. Based on lessons learned from the challenge, we emphasize the significance of open research practices, mentorship, transparency guidelines, as well as the use of technologies such as executable research objects for the reproduction of geoscientific published research. We propose a supportive framework of tools and infrastructure for evaluating reproducibility in geoscientific publications, with a case study for the climate informatics community. While the recommendations focus on future CIRCs, we expect they would be beneficial for wider umbrella of reproducibility initiatives in geosciences. |
| format | Article |
| id | doaj-art-99e576a583a947fc92db7c4fb45924c9 |
| institution | Kabale University |
| issn | 2634-4602 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Environmental Data Science |
| spelling | doaj-art-99e576a583a947fc92db7c4fb45924c92025-01-22T09:46:23ZengCambridge University PressEnvironmental Data Science2634-46022025-01-01410.1017/eds.2024.35Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate scienceAlejandro Coca-Castro0https://orcid.org/0000-0002-9264-1539Anne Fouilloux1https://orcid.org/0000-0002-1784-2920Ricardo Barros Lourenço2https://orcid.org/0000-0002-4158-3244Andrew McDonald3https://orcid.org/0000-0001-9994-2476Yuhan Rao4https://orcid.org/0000-0001-6850-3403J. Scott Hosking5https://orcid.org/0000-0002-3646-3504Environment and Sustainability Grand Challenge, The Alan Turing Institute, London, UKSimula Research Laboratory, Oslo, NorwaySchool of Earth, Environment & Society, McMaster University, Hamilton, ON, CanadaDepartment of Engineering, University of Cambridge, Cambridge, UK British Antarctic Survey, NERC, UKRI, Cambridge, UKNorth Carolina Institute of Climate Studies, North Carolina State University, Asheville, NC, USAEnvironment and Sustainability Grand Challenge, The Alan Turing Institute, London, UK British Antarctic Survey, NERC, UKRI, Cambridge, UKIn this paper, we explore the crucial role and challenges of computational reproducibility in geosciences, drawing insights from the Climate Informatics Reproducibility Challenge (CICR) in 2023. The competition aimed at (1) identifying common hurdles to reproduce computational climate science; and (2) creating interactive reproducible publications for selected papers of the Environmental Data Science journal. Based on lessons learned from the challenge, we emphasize the significance of open research practices, mentorship, transparency guidelines, as well as the use of technologies such as executable research objects for the reproduction of geoscientific published research. We propose a supportive framework of tools and infrastructure for evaluating reproducibility in geoscientific publications, with a case study for the climate informatics community. While the recommendations focus on future CIRCs, we expect they would be beneficial for wider umbrella of reproducibility initiatives in geosciences.https://www.cambridge.org/core/product/identifier/S2634460224000359/type/journal_articleclimate informaticscomputational researchnotebooksreproducible researchreproduction assessment |
| spellingShingle | Alejandro Coca-Castro Anne Fouilloux Ricardo Barros Lourenço Andrew McDonald Yuhan Rao J. Scott Hosking Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science Environmental Data Science climate informatics computational research notebooks reproducible research reproduction assessment |
| title | Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science |
| title_full | Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science |
| title_fullStr | Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science |
| title_full_unstemmed | Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science |
| title_short | Improving the reproducibility in geoscientific papers: lessons learned from a Hackathon in climate science |
| title_sort | improving the reproducibility in geoscientific papers lessons learned from a hackathon in climate science |
| topic | climate informatics computational research notebooks reproducible research reproduction assessment |
| url | https://www.cambridge.org/core/product/identifier/S2634460224000359/type/journal_article |
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