Strategic implementation

Work with automation and interoperable connections between systems

Automated and interoperable information flows between relevant research information systems should be pursued, for example between data repositories, CRIS systems, data management planning tools and other administrative systems. Preventing manual duplication of work for researchers as well as research support staff should be a set goal.

Why?

Lack of integration and interoperability between systems leads to repeated manual entries, varying metadata quality and difficulties in tracking data publications. Automated and standardised workflows improve traceability, quality and efficiency and reduce the administrative burden for both researchers and supporting functions.

Establish a local routine to curate and monitor data publications

A recurring local routine to curate and monitor data publications should be established. The routine should be based on a short, locally defined threshold for what is considered “traceable enough”.

Why?

A recurring routine makes traceable datasets visible locally and helps identify recurring metadata and workflow gaps.

How?

• Define a minimal set of local criteria for what you will monitor and follow up (start small and adjust over time)
• Pull research data metadata (via soma data aggregator tool) and curate what meets the threshold.
• Log the most common reasons others don’t meet it and address them over time.

Make data publications visible and recognised in academic assessment

Research organisations should ensure that data publications can be made visible and taken into account in local processes for academic assessment, monitoring, and research evaluation—particularly where the data publications are of high quality and comply with the FAIR principles.

Why?

When data publications are not recognised as research contributions, work on them tends to be given low priority. The lack of clear incentives is a known barrier to both data publication and good research data management. Enabling data publications to be considered in evaluation contexts creates better conditions for long-term change.