Identify and promote best practices for data curation as part of good scientific practice

From GRDI2020

This is a GRDI recommendation; return to Main Page with all the challenges or to recommendations

Context and Challenges

Adequate practices for data curation is increasingly acknowledged and have become part of good scientific practice. Goals for data curation include the verifiability of research results, reproducability of research, as well as the reuse of research data.

However, data curation is essentially specific to the specific field of research. Although data infrastructure can support data curation practices, there is no generic way of addressing and "solving" data curation for all communities.

Instead, communities need to define for them individually what data curation in their specific research context means. Already numerous relevant guides have emerged that can guide the implementation in communities and getting each individual researcher on board:

• UK Data Archive
• ANU Data Management Manual
• CIESIN - Guide to managing geospatial electronic records
• DISC-UK: Policy-making for Research Data in Repositories: A Guide
• Monash Research data management guidelines
• MIT Subject Guide
• UK DCC Lifecycle Model

Recommendation

Implement and promote best practices for data management as part of good scientific practice. This includes

• descriptions of data (i.e. metadata)
• quality assurance for data and metadata
• preparing research data such that it is comprehensible for a future "desginated community" (cf. the OAIS Reference Model)
• capturing the tacit knowledge in a community (cf. theories of "organisational learning")

Stakeholders and Impact

Best practices for data curation potentially raise significantly the quality of research data, and enable collaboration across research groups and disciplines. Influential stakeholders within a community or Translator Role can trigger the creation of best practices within a research discipline. Also, funders can trigger respective developments (cf. Link data management and grant process).