Data Management Planning
GFBio aims at supporting individual researchers during all stages of their career, research groups, and large projects to develop and implement effective data management strategies for FAIR (Findable, Accessible, Interoperable, and Re-usable) data as part of good scientific practice.
A well-structured Data Management Plan (DMP) clarifies how and what data will be created, processed and documented. It names means of data archiving and publication regarding costs, as well as access conditions to the scientific community or the public. DMPs are increasingly required as a mandatory proposal part by funding agencies. Participating in the Horizon 2020 Open Research Data Pilot, for example, already requires a DMP. The German Science Foundation (DFG) demands information on data handling (DFG Proposal Preparation Instructions) and individual working groups highly recommend the introduction of data management plans for projects / proposals by default (Guidelines on the Handling of Research Data in Biodiversity Research).
But DMPs are more than just a piece of paper meant to satisfy your funder. They help you asking all the right questions concerning data management and avoiding mistakes. DMPs can accompany your research and they are not cast in stone - you can adjust your plan to your work if necessary, make it more specific and add new aspects.
Have a look at The what, why and how of data management planning in the following video (Research Data Netherlands, YouTube).
Writing a DMP
Writing a DMP is a good way of facing up your specific research data requirements and should always be carried out before you start a new project. You can also write a DMP for a running project in order to optimize your data management - there might be aspects you hadn't considered so far.
There is nothing like a Master DMP. According to your needs, a DMP can be a short summary of the central aspects of your data management but it can also be a very detailed plan including schedules for data backups and data publications. Anyway, there are some general aspects which each DMP should capture.
Provide some general information about your project.
- What's the project name?
- What is your reserach field?
- What will your project look like - e.g. will you do any field work or laboratory work?
- Who are the principal investigators?
- Who is the point of contact for the project data?
- Which data management policies or guidelines will you follow?
Describe what your research data will look like.
- What data formats will you create?
- Will your data formats be openly documented?
- Will you collect sequence data?
- Will you also collect physical objects which need to be archived?
- How much data volume and how many files will you create?
- What standards, methodologies or tools will you use?
Describe your way of documentation (metadata).
- What metadata will accompany your data?
- Which standards will your metadata have to meet?
Think about ethics and legal compliance.
- Will you create any sensitive data (e.g. personally identifiable information, information related to the Red List or the Nagoya Protocol)?
- How will your data be liscensed for reuse?
These might be the questions to start with on your way to your DMP. Furthermore, a DMP should contain information about backup practice, security issues, collaboration, data transfer (e.g. in case of field work) and moreover contain a data management cost estimation. Some helpful material might be DCC's DMP checklist or the WissGrid Checkliste zum Forschungsdaten-Management (only in German).
GFBio supports you
Contact us for support in preparing your personal data management plan.
We give advice concerning data management policies and data access rules, estimate data management costs and efforts and provide a roadmap for your long-term data availability. Furthermore, we offer reviewing of your DMP regarding special requirements of your funding agency. At the moment, we are working on a customized DMP tool which will support GFBio users in writing a DMP.