Belmont Forum Data Management Plan Scorecard

Bishop, Bradley Wade; Ungvari‐Martin, Judit; Davis, Rowena; Lee, Tina; Goudeseune, Lise; Virapongse, Arika; Samors, Robert

doi:10.5281/zenodo.3530933

Cited by 2 publications

(3 citation statements)

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“…Twenty-one DMPs (13 DMPs from the Transdisciplinary Research for Ocean Sustainability (https://www.belmontforum.org/cras/#oceans2018); abbreviated here 'Oc#') and 8 DMPs from the Resilience in Rapidly Changing Arctic Systems (https://www.belmontforum.org/ cras/#arctic2019); abbreviated here 'Ar#') from projects funded by the Belmont Forum were analyzed. These DMPs were submitted to the Belmont Forum, which had published information about DMP expectations, including a scorecard (Belmont Forum 2018) for researchers to selfevaluate their DMPs (Bishop et al 2019). The sample of this study is the entire population of DMPs from the 21 funded projects in these two categories.…”

Section: Methodsmentioning

confidence: 99%

Data Management Plans: Implications for Automated Analyses

Pham

Sandy

Bishop

et al. 2023

Data Science Journal

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Data management plans (DMPs) are an essential part of planning data-driven research projects and ensuring long-term access and use of research data and digital objects; however, as text-based documents, DMPs must be analyzed manually for conformance to funder requirements. This study presents a comparison of DMPs evaluations for 21 funded projects using 1) an automated means of analysis to identify elements that align with best practices in support of open research initiatives and 2) a manuallyapplied scorecard measuring these same elements. The automated analysis revealed that terms related to availability (90% of DMPs), metadata (86% of DMPs), and sharing (81% of DMPs) were reliably supplied. Manual analysis revealed 86% (n = 18) of funded DMPs were adequate, with strong discussions of data management personnel (average score: 2 out of 2), data sharing (average score 1.83 out of 2), and limitations to data sharing (average score: 1.65 out of 2). This study reveals that the automated approach to DMP assessment yields less granular yet similar results to manual assessments of the DMPs that are more efficiently produced. Additional observations and recommendations are also presented to make data management planning exercises and automated analysis even more useful going forward.

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Section: Methodsmentioning

confidence: 99%

Data Management Plans: Implications for Automated Analyses

Pham

Sandy

Bishop

et al. 2023

Data Science Journal

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“…In response, the Belmont Forum developed an e-Infrastructures and Data Management Toolkit (Belmont Forum e-I&DM CRA 2018) that includes a rubric for researchers preparing a Data and Digital Outputs Management Plan (D(DO)MP) for proposal submission, plus data management webinars and guidelines (Bishop et al 2019). Once a project is awarded, the Belmont Forum specifies that the D(DO)MP should be a living, actively updated document describing the management lifecycle for the data and other digital outputs to be collected, reused, processed, and/or generated.…”

Section: The Genesis Of the Belmont D(do)mpmentioning

confidence: 99%

“…For example, it quickly became clear that the D(DO) MP is substantial (~20 pages) and unwieldy for regular use by busy researchers, so a reference summary of resources was added to the 2021 version (Stall et al 2021b) and modified later (e.g., Stall et al 2023b). As we moved through the project, we added several important items to the Belmont Forum rubric (Bishop et al 2019). These included processes that would help to ensure the quality of digital objects during the life of the project and prior to preservation, support for inclusive collaboration and authorship for data and digital outputs, guidance for giving attribution for data and digital outputs previously created or created by others, and suggested decisions for project backup and closeout (Stall et al 2023a).…”

Section: The Evolving Content Of the Parsec D(do)mpmentioning

confidence: 99%

The Value of a Data and Digital Object Management Plan (D(DO)MP) in Fostering Sharing Practices in a Multidisciplinary Multinational Project

Specht,

O’Brien,

Edmunds

et al. 2023

Data Science Journal

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Data Management Plans (DMP) are now a routine part of research proposals but are generally not referred to after funding is granted. The Belmont Forum requires an extensive document, a 'Data and Digital Object Management Plan' (D(DO)MP) for its awarded projects that is expected to be kept current over the life of the project. The D(DO)MP is intended to record team decisions about major tools and practices to be used over the life of the project for data and software stewardship, and for preservation of data and software products, aligned with the desired Open Science outcomes relevant to the project. Here we present one of the first instances of the use of Belmont's D(DO)MP through a case study of the PARSEC project, a multinational and multidisciplinary investigation of the socioeconomic impacts of protected areas.We describe the development and revision of our interpretation of the D(DO)MP and discuss its adoption and acceptance by our research group. We periodically assessed the data management sophistication of team members and their use of the various nominated tools and practices. As a result, for example, we included summaries to enable the key components of the D(DO)MP to be readily viewed by the researcher. To meet the Open Science outcomes in a complex project like PARSEC, a comprehensive and appropriately structured D(DO)MP helps project leaders (a) ensure that team members are committed to the collaboration goals of the project, (b) that there is regular and effective feedback within the team, (c) training in new tools is provided as and when needed, and (d) there is easy access to a short reference to the tools and descriptions of the nominated practices.

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Belmont Forum Data Management Plan Scorecard

Cited by 2 publications

References 0 publications

Data Management Plans: Implications for Automated Analyses

Data Management Plans: Implications for Automated Analyses

The Value of a Data and Digital Object Management Plan (D(DO)MP) in Fostering Sharing Practices in a Multidisciplinary Multinational Project

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