Sharing data and code facilitates reproducible and impactful research

Author:

Baker Jack W1ORCID,Crowley Helen2ORCID,Wald David3ORCID,Rathje Ellen4,Au Siu-Kui5ORCID,Bradley Brendon A6ORCID,Burton Henry7,Cabas Ashly8ORCID,Cattari Serena9,Cauzzi Carlo10ORCID,Cavalieri Francesco11ORCID,Contreras Santina12,Costa Rodrigo13ORCID,Eguchi Ronald T14,Lallemant David5ORCID,Lignos Dimitrios G15,Maurer Brett W16,Molina Hutt Carlos17ORCID,Sextos Anastasios1819ORCID,Seyhan Emel20,Silva Vitor21ORCID,Sucuoğlu Haluk22,Taciroglu Ertugrul7ORCID,Thompson Eric M3ORCID

Affiliation:

1. Stanford University, Stanford, CA, USA

2. Global Earthquake Model, Pavia, Italy

3. U.S. Geological Survey, Golden, CO, USA

4. University of Texas, Austin, Austin, TX, USA

5. Nanyang Technological University, Singapore, Singapore

6. University of Canterbury, Christchurch, New Zealand

7. University of California Los Angeles, Los Angeles, CA, USA

8. North Carolina State University, Raleigh, NC, USA

9. University of Genova, Genova, Italy

10. ORFEUS and SED-ETHZ, Zürich, Switzerland

11. Eucentre Foundation, Pavia, Italy

12. University of Southern California, Los Angeles, CA, USA

13. University of Waterloo, Waterloo, ON, Canada

14. ImageCat, Inc., Long Beach, CA, USA

15. École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

16. University of Washington, Seattle, WA, USA

17. University of British Columbia, Vancouver, BC, Canada

18. University of Bristol, Bristol, UK

19. National Technical University of Athens, Athens, Greece

20. Moody’s RMS, Newark, CA, USA

21. University of Aveiro, Aveiro, Portugal

22. Middle East Technical University, Ankara, Turkey

Abstract

Modern research often involves the collection or analysis of data and the use of specialized computer algorithms. Traditional text articles thus provide only partial documentation of a research study. Readers have limited ability to reproduce or utilize work if the source data are not available or if it relies on an algorithm that is described, but code is not provided. Fortunately, a wide variety of tools are now available to support the publication of research data and code. The effort required to publish data is now relatively small, and the benefits can be immense. This opinion article discusses trends toward increased sharing in academic publishing. It describes opportunities and resources to support data and code sharing and describes the benefits for both authors and readers. Finally, it discusses how Earthquake Spectra is providing resources and enhancing its policies to establish the sharing of data as the default procedure when publishing in the journal, and encourage the sharing of code and other resources.

Publisher

SAGE Publications

Reference37 articles.

1. AGU (2024) Data & software for authors. Available at: https://www.agu.org/Publish-with-AGU/Publish/Author-Resources/Data-and-Software-for-Authors (accessed 10 February 2024).

2. PAGER-CAT: A Composite Earthquake Catalog for Calibrating Global Fatality Models

3. ASCE (2024) Publishing in ASCE journals: Data sharing. Available at: https://ascelibrary.org/author-center/journal#data-sharing (accessed 10 February 2024).

4. Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards

5. Next-generation liquefaction database

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