RDM+PM Checklist: Towards a Measure of Your Institution’s Preparedness for the Effective Planning of Research Data Management

Article


Bellgard, M., Bennett, R., Wyborn, Y., Williams, C., Barner, L. and Zeps, N. 2023. RDM+PM Checklist: Towards a Measure of Your Institution’s Preparedness for the Effective Planning of Research Data Management. Data Science Journal. 22 (Art. 36). https://doi.org/10.5334/dsj-2023-036
AuthorsBellgard, M., Bennett, R., Wyborn, Y., Williams, C., Barner, L. and Zeps, N.
Abstract

A review at our institution and a number of other Australian universities was conducted to identify an optimal institutional-wide approach to Research Data Management (RDM). We found, with a few notable exceptions, a lack of clear policies and processes across institutes and no harmonisation in the approaches taken. We identified limited methods in place to cater for the development of Research Data Management Plans (RDMPs) across different disciplines, project types and no identifiable business intelligence (BI) for auditing or oversight. When interviewed, many researchers were not aware of their institution’s RDM policy, whilst others did not understand how it was relevant to their research. It was also discovered that primary materials (PM), which are often directly linked to the effective management of research data, were not well covered. Additionally, it was unclear in understanding who was the data custodian responsible for overall oversight, and there was a lack of clear guidance on the roles and responsibilities of researchers and their supervisors. These findings indicate that institutions are at risk in terms of meeting regulatory requirements and managing data effectively and safely. In this paper, we outline an alternative approach focusing on RDM ‘Planning’ rather than on RDMPs themselves. We developed simple-to-understand guidance for researchers on the redeveloped RDM policy, which was implemented via an online ‘RDM+PM Checklist’ tool that guides researchers and students. Moreover, as it is a structured tool, it provides real-time business intelligence that can be used to measure how compliant the organisation is and ideally identify opportunities for continuous improvement.

JournalData Science Journal
Journal citation22 (Art. 36)
ISSN1683-1470
Year2023
PublisherUbiquity Press for the Committee on Data for Science and Technology
Publisher's version
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Anyone
Digital Object Identifier (DOI)https://doi.org/10.5334/dsj-2023-036
Publication dates
Online29 Sep 2023
Publication process dates
Accepted22 Jun 2023
Deposited04 Oct 2023
FunderQueensland University of Technology
Copyright holder© 2023, The Authors
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