Data Management Plans
Quality assured and correct data management is often facilitated by a well-thought-out data management plan (DMP). Many funders in Europe and the US require that you submit a data management plan. This currently applies to the Swedish Research Council, Horizon 2020, European Research Council (ERC) and some US-funded projects.
The Swedish Research Council
Researchers at KI who are awarded grant funding from 2019 and onwards shall write a data management plan for their project. You don’t have to submit the plan to the Swedish Research Council, but it should be in place when you start your project and it is important that you keep it updated during the project.
The following description is direct instructions from the Swedish Research Council on what a Data Management Plan (DMP) should contain:
- Description of data – reuse of existing data and/or production of new data:
- How will data be collected, created or reused?
- What types of data will be created and/or collected, in terms of data format and amount/volume of data?
- Documentation and data quality:
- How will the material be documented and described, with associated metadata relating to structure, standards and format for descriptions of the content, collection method, etc.?
- How will data quality be safeguarded and documented (for example repeated measurements, validation of data input, etc.)?
- Storage and backup:
- How is storage and backup of data and metadata safeguarded during the research process?
- How is data security and controlled access to data safeguarded, in relation to the handling of sensitive data and personal data, for example?
- Legal and ethical aspects:
- How is data handling according to legal requirements safeguarded, e.g. in terms of handling of personal data, confidentiality and intellectual property rights?
- How is correct data handling according to ethical aspects safeguarded?
- Accessibility and long-term storage:
- How, when and where will research data or information about data (metadata) be made accessible? Are there any conditions, embargoes and limitations on the access to and reuse of data to be considered?
- In what way is long-term storage safeguarded, and by whom? How will the selection of data for long-term storage be made?
- Will specific systems, software, source code or other types of services be necessary in order to understand, partake of or use/analyse data in the long term?
- How will the use of unique and persistent identifiers, such as a Digital Object Identifier (DOI), be safeguarded?
- Responsibility and resources:
- Who is responsible for data management and (possibly) supports the work with this while the research project is in progress? Who is responsible for data management, ongoing management and long-term storage after the research project has ended? What resources (costs, labour input or other) will be required for data management (including storage, back-up, provision of access and processing for long-term storage)? What resources will be needed to ensure that data fulfil the FAIR principles?
Swedish National Data Service (SND): Checklist for a Data Management Plan. The checklist is a translation of the SND's checklist in Swedish, which contains more extensive information for each element.
Swedish version: Checklista för datahanteringsplan
The Association of Swedish Higher Education Institutions (SUHF): Recommendations for a data management plan / Rekommendation för datahanteringsplan (Swedish only)
From 2017 all H2020 projects are covered by the “Open Research Data Pilot” (ORD). This means that all H2020 projects granted from 2018 and onwards shall submit a Data Management Plan (DMP) 6 months after the project has started, at the latest.
See below about opting out from the Open Research Data Pilot.
A Data Management Plan for a H2020 project shall describe how you manage your research data during its whole life cycle. As a part in making your data FAIR your DMP should describe
- The handling of research data during & after the end of the project
- What data will be collected, processed and/or generated
- Which methodology & standards will be applied
- Whether data will be shared/made open access
- How data will be curated & preserved (including after the end of the project).
Sensitive data – ”Opt out”
Research projects within H2020 could withdraw from making its data openly available (Open Access). It is called “opt out” and concerns data that for various reasons are sensitive or eg. confidential.
Costs associated with open access to research data, including the creation of the data management plan, can be claimed as eligible costs of any Horizon 2020 grant.
European Research Council (ERC)
For ERC projects participating in the EU ORD pilot, the data management plan must address following issues:
- Making data Findable
- Making data openly Accessible
- Making data Interoperable
- Increase data Re-use
- Allocation of recourses and data security
The data management plan will also have to specify if certain datasets remain closed and the reasons for not giving access should be given.
The FAIR principles
EU and Horizon 2020 specifies that research data should meet the “FAIR principles”. In December 2018 the Swedish Research Council also published the report “Criteria for FAIR research data".
The concept FAIR means that data should be