This study is about research data management and also appraisal and selection. This is an issue that has become more significant in recent years as volumes of data have grown. "The purpose is to provide new insights that will be useful to institutions, research funders, researchers, publishers, and Jisc on what research data to keep and why, the current position, and suggestions for improvement."
"Not all research data is the same: it is highly varied in terms of data level; data type; and origin. In addition, not all disciplines are in the same place or have identical needs."
"It is essential to consider not only What and Why to keep data, but for How Long to keep it, Where to keep it, and increasingly How to keep it in ways that reflects its potential value, cost, and available funding."
The study lists ten recommendations:
- Consider what is transferable between disciplines. Support adoption of effective practice via training, technologies, case studies, and guidance checklists.
- Bring communities together with workshops to evolve disciplinary norms
- Harmonise funder requirements for research data where relevant
- Investigate the costs and benefits of curation levels, storage, or appraisal for what to keep f
- Implement the FAIR principles as appropriate for kept data.
- Enhance data discoverability and identification of data by recording and to identifying data generated by research projects in existing research databases.
- Require Data Access Statements in all published research articles where data is used as evidence, and encourage adoption of the Transparency and Openness Promotion (TOP) guidelines
- Improve incentives and lower the barriers for data sharing.
- Increase publisher and funder collaborations around research data.
- Improve communication on what research data management costs can be funded and by whom
Other notes from the study:
Costs of research data management seen as too high
Obsolescence of data format or software
The volume of research data and the number of new research data services and repositories is increasing.
"The high-level principles for research data management may be established but the everyday practice and procedures for the full-range of research data, what and why to keep, for how long, and where and how to keep it, are still evolving."
“All those engaged with research have a responsibility to ensure the data they gather and generate is properly managed, and made accessible, intelligible, assessable and usable by others unless there are legitimate reasons to the contrary. Access to research data therefore carries implications for cost and there will need to be trade-offs that reflect value for money and use.”
The Core Trustworthy Data Repositories Requirements notes four curation levels that can be performed by trusted repositories:
a. As deposited
b. Basic curation eg, brief checking, addition of basic metadata or documentation
c. Enhanced curation eg, conversion to new formats, enhancement of documentation
d. Data level curation (as in C above, with additional editing of data for accuracy)