There is strong agreement across the sciences that replicable workflows are needed for computational modeling. Open and replicable workflows not only strengthen public confidence in the sciences, but also result in more efficient community science. However, the massive size and complexity of geoscience simulation outputs, as well as the large cost to produce and preserve these outputs, present problems related to data storage, preservation, duplication, and replication. The simulation workflows themselves present additional challenges related to usability, understandability, documentation, and citation. These challenges make it difficult for researchers to meet the bewildering variety of data management requirements and recommendations across research funders and scientific journals. This paper introduces initial outcomes and emerging themes from the EarthCube Research Coordination Network project titled “What About Model Data? - Best Practices for Preservation and Replicability,” which is working to develop tools to assist researchers in determining what elements of geoscience modeling research should be preserved and shared to meet evolving community open science expectations. Specifically, the paper offers approaches to address the following key questions: • How should preservation of model software and outputs differ for projects that are oriented toward knowledge production vs. projects oriented toward data production? • What components of dynamical geoscience modeling research should be preserved and shared? • What curation support is needed to enable sharing and preservation for geoscience simulation models and their output? • What cultural barriers impede geoscience modelers from making progress on these topics?
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This content will become publicly available on November 1, 2024
What about Model Data? Best Practices for Preservation and Replicability
It has become common for researchers to make their data publicly available to meet the data management and accessibility requirements of funding agencies and scientific publishers. However, many researchers face the challenge of determining what data to preserve and share and where to preserve and share those data. This can be especially challenging for those who run dynamical models, which can produce complex, voluminous data outputs, and have not considered what outputs may need to be preserved and shared as part of the project design. This manuscript presents findings from the NSF EarthCube Research Coordination Network project titled “What About Model Data? Best Practices for Preservation and Replicability” (
- Award ID(s):
- 1929757
- NSF-PAR ID:
- 10477877
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Bulletin of the American Meteorological Society
- Volume:
- 104
- Issue:
- 11
- ISSN:
- 0003-0007
- Page Range / eLocation ID:
- E2053 to E2064
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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