Data management plan
A data management plan, or DMP, is a document where information about the data management in a research project is collected. The plan covers all phases of the project, from planning and collection, production or generation of data, to analysis, publication, and archiving. The idea is that you start writing a DMP when you apply for research funding or plan a research project, and then develop and update the plan as needed. You can also create a plan for a project that is already in progress. What the plan will contain in more detail depends on the research topic and the nature of the project. The intention is that the DMP should be a “living” document, which is kept up to date throughout the project.
The main purpose of data management plans is to enable different stakeholders to find the right information when they need it. A DMP can also make it easier to meet the FAIR data principles, and to keep track of data during the research process. This means that the data management plan has several purposes, associated with different stakeholders:
- Preservation and future research: archives and data repositories regard the DMP as a way to make researchers plan for long-term preservation of research data, and to describe data in a manner that makes them reusable for other researchers. Research funders, and society as a whole, regard the reuse of data as a way to get maximum output from the taxpayers’ money, as that is how data collection and data production is generally funded.
- Preparation and legal requirements: IT Services in higher education institutions need to know what a research project requires for their data storage. Administrators who are responsible for making sure that research data are managed according to current legislation (such as heads of departments and data protection officers) need to know which data exist and how they will be managed.
- Support and training: many stakeholders experience a lack of knowledge about the correct ways to manage and document research data. To them, the DMP is a useful tool to support and train researchers in these matters.
- Research efficiency: it is assumed that deliberate and well-planned research data management creates order among project data. This would lead to fewer time-consuming mistakes and less time spent on trying to find project information and the right versions of data and documents.
Data management plans can be a requirement from various stakeholders. Most common, today, is that research funders demand that a DMP is either submitted as part of the application for funding, or created when a project that has been granted funding begins (or both). For example, the Swedish Research Council and Formas both require that you include a DMP in your research project. A plan that is submitted with an application can be quite short and then develop into a fuller DMP once the project begins. HEIs can also require data management plans, and in some research fields it is becoming standard practice to use a DMP, as well as how a DMP is supposed to be structured. Usually, the stakeholder behind the requirement has a general idea of what they want the data management plan to contain, either given in specific instructions, or by reference to guides, templates, or checklists produced by other organizations. The Swedish Research Council offers access to one of the digital DMP tools, DMP Online. As a researcher, you have access to the tool if your HEI or organization has decided that DMP Online is what they want to use to produce and maintain data management plans. You can ask your local research data support unit if you have access to this resource. Further down on this page you can find links to some more resources that may be of help when you write a data management plan.
The SND Checklist for Data Management Plan
SND has developed a DMP checklist to support researchers in writing a data management plan. It may appear very extensive, as we have divided sections that other templates have grouped together in one category; we have chosen to explain, in some detail, which information is needed and why; and the DMP is intended to be useful in any research discipline. (The latter means that if some information seems irrelevant to your project, it may very well be so.)
The data management plan contains seven main sections, associated with how research data are managed in projects:
- An overview of the project, such as primary investigator, which higher education institution is the research principal, and who in the project team is responsible for what (including to keep the DMP up to date).
- Management of data deemed worthy of protection, which may contain personal data, information about archaeologically or biologically sensitive locations, data about military objectives etc. Do you need to plan for how to manage these types of data in order to make sure that they don’t fall into the wrong hands? Do you use copyrighted data; if so, how will you manage them?
- A plan for data collection and production, including to investigate whether there already are datasets produced by others, which can be used in the project.
- How are you going to document the data material, and according to which routines? Are there any standardized descriptions which are used in your research field?
- How are you going to organize the data with appropriate file names and logical folder structures? What are you going to do with different versions of datasets? The idea is to make it easy to find the right data. How will you make sure that data are stored in a suitable manner and backed up often and securely enough?
- There are cost associated with data management, in terms of staff/time, storage, and possibly even for specific software or hardware. If you budget for these costs right from the start, the costs for data management can be included in a possible funding application.
- How can the data be preserved and made accessible? How are you going to describe them, which prerequisites are there – are there any restrictions on sharing the data? You may early on in the project want to contact the data repository where you plan to make the data accessible, and consult with them on what they request and recommend.
You can download the checklist in English or Swedish, in pdf format and editable formats.
Some resources when you write a data management plan
The resources in this list may be of help when you develop your own data management plan. You can also consult with your local data support unit to see of there are specific resources in your HEI.
- The SND Checklist for Data Management Plan
- The Swedish Research Council’s overview of central parts of a data management plan
- The CESSDA ERIC data management support Data Management Expert Guide
- Guidelines on FAIR Data Management in Horizon 2020, including information on data management plans.