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Data for Authors

What is needed

The data that supports your research and the visualizations in your paper must be deposited in a trusted repository that supports the FAIR principles. When identifying the most appropriate repositories for your data, please consider the following prioritization.  We recommend a repository that specializes in the data for your scientific domain as this will maximize the probability that the deposited data will be interoperable and reusable.  If that is not available for your data type, next is your institutional repository, your computing center, and finally a general repository.  Please note that the repository you select must offer a translation to English in order to comply. 

AGU partners with Dryad

Starting March 2021, AGU authors funded by the U.S. NSF will have their data publication fees waived when using the Dryad repository. The fee is waived only when authors select an AGU journal. For AGU authors, a general data repository like Dryad is a great choice if a discipline-specific repository is not available for the type of data used in their research.

All datasets in Dryad are curated to meet data and metadata curation requirements. Datasets deposited in Dryad are mandate-compliant with U.S. NSF and AGU data publication requirements. For more information on using Dryad, please visit the Dryad data submission process page and any questions on submitting should be directed to [email protected].

AGU has partnered with Dryad on an NSF Grant (2025364) to pilot this program. Contact [email protected] with any questions about this pilot.

Journal-Specific Data Guidance

Please note that only those journals marked with an asterisk (*) are available at this time.

AGU Advances - Open Access         Journal of Geophysical Research: Atmospheres
Earth and Space Science - Open Access         Journal of Geophysical Research: Biogeosciences*
Earth's Future - Open Access         Journal of Geophysical Research: Earth Surface
Geochemistry, Geophysics, Geosystems*         Journal of Geophysical Research: Oceans
GeoHealth - Open Access*         Journal of Geophysical Research: Planets
Geophysical Research Letters         Journal of Geophysical Research: Solid Earth*
Global Biogeochemical Cycles         Journal of Geophysical Research: Space Physics
Journal of Advances in Modeling Earth Systems (JAMES) - Open Access          
Paleoceanography and Paleoclimatology          
Radio Science          
Reviews of Geophysics [Invitation only]          
Space Weather - Open Access          
Water Resources Research*          

Data availability statement examples

For each dataset that supports your research, both a citation and a data availability statement must be present. The data availability statement for each data set must be included in the Open Research section of your paper indicating where readers can access the data. See the information on data citation for additional guidance. The availability statement should include an in-text citation, licensing information, and access restrictions. Statements to the effect of "data available from authors" are not acceptable.

Common templates for data availability statements:

  • 1
    For data stored in a repository: Datasets for this research are available in these in-text data citation references: Smith et al. (2019), [with this license, and these access restrictions if any], Jones et at. (2017) [with this license, and these access restrictions if any].
  • 2
    For data published in the literature: Datasets for this research are included in this paper (and its supplementary information files): [citation for paper] or point to where the references are compiled.
  • 3
    For technical reports publishing the description of a dataset and its preparation, e.g. a data paper. Datasets for this research are described in this paper: [citation for paper, with this license, and these access restrictions if any].
  • 4
    For theoretical papers, or most review papers: Data were not used, nor created for this research.
  • 5
    For data not publicly available, but available to researchers with appropriate credentials: Data for this research are not publicly available due to [Fill in reasons]. Data are stored in this in-text data citation reference: Smith et al. (2019), [with this license, and these access restrictions if any].
  • 6
    For data that are restricted by commercial, industry, patent, government policies, regulations, or laws: Data supporting this research are available in [cite in-text data citation reference from third party source], with [these restrictions that include information concerning required NDA, licensing, agreements], and are not accessible to the public or research community. [Provide process for how other researchers can gain access.] NOTE: If your data are in this category, the editors will determine if this statement meets the AGU data guidelines sufficiently.
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Data citations

Your data citation(s) should include the data used in your paper. This may include data that others have created, new data as a result of your research, and processed data used for your analysis. It is especially important that new data are placed in a domain repository. For guidance on how best to format a compliant data citation along with examples, reference ESIP’s Data Citation Guidelines For Earth Science Data.
  • 1
    Cline, D., R. Armstrong, R. Davis, K. Elder, and G. Liston. 2003. CLPX-Ground: ISA snow depth transects and related measurements ver. 2.0. Edited by M. A. Parsons and M. J. Brodzik. NASA National Snow andIce Data Center Distributed Active Archive Center. https://doi.org/10.5060/D4MW2F23. Accessed 2008-05-14. *Reproduced from ESIP
  • 2
    Maslanik, J. and J. Stroeve. 1999, updated daily. Near-Real-Time DMSP SSMIS Daily Polar Gridded Sea Ice Concentrations, Version 1. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/U8C09DWVX9LM. Accessed 2019-02-14. *Reproduced from ESIP
  • 3
    Lynch, L., M. Machmuller, C. Boot, T. Covino, C. Rithner, et al. 2019. Dissolved organic matter chemistry and transport along an Arctic tundra hillslope, Imnavait Creek Watershed, Alaska, 2018. Arctic Data Center. https://doi.org/10.18739/A2RF5KF5N. Accessed 2019-02-28. *Reproduced from ESIP
  • 4
    Moschetti, M. P., 2017, Database of earthquake ground motions from 3-D simulations on the Salt Lake City of the Wasatch fault zone, Utah: U.S. Geological Survey data release. https://doi.org/10.5066/F7V98691. Accessed 2019-02-28. *Reproduced from ESIP
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  • 1 Domain Repository

    For your new data, we recommend a repository that specializes in the data for your scientific domain as this will maximize the probability that the deposited data will be interoperable and reusable. See Section 1 of repository FAQs for more details.
  • 2 Institutional Repository

    Many universities are supporting research data management on campus, and such services are often provided through the library. Librarians can be an excellent source of research data management support, including repository selection, and can help you comply with funder, publisher, and university requirements.
  • 3 Computing Center

    High Performance Computers (HPC) have infrastructure to support research using models and simulations, which may be involved in generating and/or analyzing high volume data. The operations team at the center may have recommendations for data management, storage and preservation.
  • 4 General Repositories

    If none of the above options are possible for your type of data, you may be able to use a general repository. Please refer to the Generalist Repository Comparison Chart for guidance. When using a general repository, make sure you provide documentation about your data that is in line with your community standards.

Guidelines for authors where research is primarily based on models

When the primary data for the research comes from model simulations, follow these guidelines:

  1. Citation of the model.
    • BEST OPTION: Cite the model using a software repository that registers the version used for the paper with a globally resolvable persistent identifiers (e.g. Digital Object Identifier) and metadata that describes the model using community standards.
    • GOOD OPTION: Cite the model, including the version information, using a general repository (e.g. Zenodo option for GitHub). The repository entry should include along with the model 1) a descriptive file (e.g. metadata) that preferably follows a standard appropriate for your community, 2) a preferred citation that accurately captures the authors/creators of the model.
    • ACCEPTABLE OPTION: Cite the publication where the model is described with information about the version used for this paper.
  2. Description of the model.
    • Include a description of the model in the text of the paper that is adequate to support reproducibility.
  3. Information about the configuration/parameters used to run the model.
    • This information should be included in the paper text as well as providing the script used. The scripted should be cited, and preserved in a trusted repository. Any forcing datasets used should be described and cited.
  4. Data that Supports the Summary Results, Tables, and Figures.
    • BEST OPTION: Cite a package in an appropriate repository that includes scripts, provenance information, and summary files that support the research, figures, and tables, consistent with archives maintained for transparency and traceability by assessments such as the IPCC.
    • GOOD OPTION: Cite files (e.g. scripts, descriptive detail) in an appropriate repository that support evaluating the research and provide the details behind the tables and figures.
    • ACCEPTABLE OPTION: Provide the necessary information for transparency and traceability of the analysis using your community standards or guidance.
  5. Model Output Data (optional).
    • If certain model output data are instrumental to evaluating the research, then deposit these in a trusted repository (see ***) that supports the FAIR Data Principles. There are currently limited resources for preserving many files of large size. Selecting representative output from one or a few model runs as is recommended by a specific community may be necessary.

      If the model is not open because of the sensitivity of the research or proprietary concerns, then provide as much information as possible to support evaluation of the research and reproducibility.
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If you have questions about how to comply with AGU data and software requirements for your manuscript, please contact us at [email protected].