Data Management Plans
Data is the most important asset. It validates a research story and a conclusions; it provides a platform of confidence for other researchers who might continue your work; and it is a resource that can be used by researchers in other fields to undertake new work, perhaps completely unrelated to your own research interests. Well-organised data that is accessible to the research community can continue to provide extended benefit and value long after your projects have been completed.
It’s important to ensure that the mode of data collection is well described—-what data will be produced in a project, and how it will be managed during the project, and how it will become/remain accessible to the scientific community after the project. The normal method for compliance with these policies is to write a Data Management Plan. The key points for inclusion are:
- What types of data will be created?
- How will these data be processed?
- How will they be stored and backed up?
- How will they be documented (inc. naming conventions, directory structures etc)?
- How will these data be of benefit to the broader scientific community?
- How will they be archived and will they comply with any data/metadata standards?
- How will they be made available and discoverable to the broader community?
- What are the policies for sharing, re-use etc?
The primary aim of Data Management Plan is to ensure that the data is collected in good manner and stored in a matter that ensure reproducible work with other activities and the work will be of benefit to the whole community.
