Denmark is one of the world leaders in digital health and knows a lot about data and data management. Today we present the report on Current Best Practice for Research Data Management Policies from May 2014 produced by the Danish e-Infrastructure Cooperation and the Danish Digital library.
The researchers conducted a survey to identify the key elements of current good practice in research data policies. So, what makes a good policy?
According to the study, each good research policy starts with the following considerations:
- An account of the general drivers and principles: these include the validation of research results, research opportunities for data reuse, the principle of open access by default to the outputs of publicly-funded research, and broader societal and economic benefits.
- A discussion of the requirements for the effective data sharing: e.g. ‘intelligent openness’ and the need for data to be ‘discoverable, accessible, assessable, intelligible, useable, and whenever possible interoperable to specific quality standards‘.
- A statement of the necessary limits of openness: these are imposed, in particular, by the need to protect personal information, by the requirement to respect commercial considerations and by security concerns.
At the core of each good policy, the following elements are present:
- A definition of research data
- An overview of the data within the scope of the policy: this includes 1) the data that directly underpin or substantiate published research findings (i.e. those required for validation) and 2) the data assets that are created by the research project, but which may not directly underpin the published research findings.
- An indicaton of general criteria for the selection of research data: it is helpful for policies to indicate which data are likely to be the most important to select for sharing
- A summary of responsibilities of funders, researchers, research organisations, and research data services/centres.
- An indication of the availability of infrastructure and responsibility for costs.
- An overview of data management planning requirements.
- Recommendations on enabling discovery and reuse.
- Stipulations to encourage recognition and reward for data providers.
- A summary of reporting requirements, compliance monitoring and any possible sanctions.
Depending on the area of research, policies have to address the following issues:
- Legal and ethical requirements specific to the type of research being conducted: e.g. privacy is particular important in health and social sciences.
- Existence of more established data infrastructure and practice. For research disciplines where international or national data centres have been established, policies more often provide lists of appropriate data centres or databases and allude to any existing technical standards or practices widely used in that discipline.
- Accepted technical approaches in a specific research area. In some areas of the social sciences, life sciences and natural or technical sciences, specific data format or metadata standards have emerged and become common practice. Where this is the case, these standards may be mentioned directly or indirectly in the policy documents and recommendations.
You can access the full report here.