Risk Assessment for Scientific Data

Matthew S. Mayernik; Kelsey Breseman; Robert R. Downs; Ruth Duerr; Alexis Garretson; Chung-Yi (Sophie) Hou; Environmental Data Governance Initiative (EDGI) and Earth Science Information Partners (ESIP) Data Stewardship Committee

doi:10.5334/dsj-2020-010

Risk Assessment for Scientific Data

Authors

Matthew S. Mayernik National Center for Atmospheric Research (NCAR), University Corporation for Atmospheric Research (UCAR) https://orcid.org/0000-0002-4122-0910
Kelsey Breseman Environmental Data & Governance Initiative (EDGI) https://orcid.org/0000-0003-1348-3139
Robert R. Downs Columbia University, Center for International Earth Science Information Network (CIESIN) https://orcid.org/0000-0002-8595-5134
Ruth Duerr Ronin Institute for Independent Scholarship https://orcid.org/0000-0003-4808-4736
Alexis Garretson George Mason University, Department of Biology, School of Systems Biology https://orcid.org/0000-0002-7260-0131
Chung-Yi (Sophie) Hou Ronin Institute for Independent Scholarship https://orcid.org/0000-0002-8087-1775
Environmental Data Governance Initiative (EDGI) and Earth Science Information Partners (ESIP) Data Stewardship Committee

DOI:

https://doi.org/10.5334/dsj-2020-010

Keywords:

risk assessment, data preservation, data stewardship, metadata

Abstract

Ongoing stewardship is required to keep data collections and archives in existence. Scientific data collections may face a range of risk factors that could hinder, constrain, or limit current or future data use. Identifying such risk factors to data use is a key step in preventing or minimizing data loss. This paper presents an analysis of data risk factors that scientific data collections may face, and a data risk assessment matrix to support data risk assessments to help ameliorate those risks. The goals of this work are to inform and enable effective data risk assessment by: a) individuals and organizations who manage data collections, and b) individuals and organizations who want to help to reduce the risks associated with data preservation and stewardship. The data risk assessment framework presented in this paper provides a platform from which risk assessments can begin, and a reference point for discussions of data stewardship resource allocations and priorities.

Downloads

Published

2020-03-12

Issue

Vol. 19 (2020)

Section

Research Papers

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms. If a submission is rejected or withdrawn prior to publication, all rights return to the author(s):

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.

Submitting to the journal implicitly confirms that all named authors and rights holders have agreed to the above terms of publication. It is the submitting author's responsibility to ensure all authors and relevant institutional bodies have given their agreement at the point of submission.

Note: some institutions require authors to seek written approval in relation to the terms of publication. Should this be required, authors can request a separate licence agreement document from the editorial team (e.g. authors who are Crown employees).