Writing a Data Management Plan

1 What is a Data Management Plan?

Data management plans (DMPs) are written, living documents that outline what researchers will do with the data during and after research projects. As the Digital Curation Centre (DCC) explains, DMPs "typically state what data will be created and how, and outline the plans for sharing and preservation, noting what is appropriate given the nature of the data and any restrictions that may need to be applied."

Funding agencies are increasingly requiring that grants include a DMP that describes how the data will be handled throughout the research lifecycle and how the data will be disseminated. Even where a plan is not required, having one formalized is good practice and can help to ensure that a research team is following the same approaches to caring for data.

2 Components of a Data Management Plan

There is a general set of elements that DMPs should address, while funder requirements for DMPs can differ:

  • Roles and responsibilities:
    • Who will be responsible for data management?
    • How will adherence to data management policies be enforced?
  • Data production and storage:
    • How and what types of research data will be produced?
    • How is the quality of the research data controlled?
    • How much research data will be produced?
    • How will research data be stored during the active phase of the project?
    • Will publicly-available research data be used (if so, from where)?
  • Data organization and documentation:
    • How will data be processed and organized?
    • What file formats will be used?
    • How will data be described or contextualized so that they can be found and re-used by others in the future?
  • Data access and sharing:
    • How will data be shared with others?
    • Will release of data be embargoed (if so, why and for how long)?
    • If data are of a sensitive nature, how will sharing be restricted and/or data processed to protect privacy?
  • Data re-use:
    • Who can re-use the data?
    • How should others re-use the data?
    • What credit should be given for data re-use?
    • Can others re-disseminate the data?
  • Data preservation:
    • Which data will be preserved?
    • How long will data be preserved?
    • Which repository/archive/database will be used?
    • How often will back-ups occur?
    • What metadata or documentation will accompany the data?

For more useful prompts, the DCC in the UK has prepared a Checklist for a Data Management Plan.

3 Data Management Plans for Funders

Many granting agencies and funders require data management plans be submitted with grant proposals. They recognize the benefits of data management planning on the integrity of research data and often have policies encouraging data sharing. These data management plans are generally no more than two pages, enough to get researchers thinking about the issues of data management in the early stages of planning when it is most effective. Some funders also require grantees to discuss how they followed their plan at the end of the grant.

4 Science Europe – Practice Guide

Science Europe, of which SNFS is a member, has published a practice guide. According to their guidance each DMP has at least to answer the following questions:

  1. Data description and collection or re-use of existing data
    1. How will new data be collected or produced and/or how will existing data be re-used?
    2. What data (for example the kinds, formats, and volumes) will be collected or produced?
  2. Documentation and data quality
    1. What metadata and documentation (for example the methodology of data collection and way of organizing data) will accompany data?
    2. What data quality control measures will be used?
  3. Storage and backup during the research process
    1. How will data and metadata be stored and backed up during the research process?
    2. How will data security and protection of sensitive data be taken care of during the research?
  4. Legal and ethical requirements, codes of conduct
    1. If personal data are processed, how will compliance with legislation on personal data and on data security be ensured?
    2. How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation is applicable?
    3. How will possible ethical issues be considered, and codes of conduct followed?
  5. Data sharing and long-term preservation
    1. How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
    2. How will data for preservation be selected, and where will data be preserved long-term (for example a data repository or archive)?
    3. What methods or software tools will be needed to access and use the data?
    4. How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data set be ensured?
  6. Data management responsibilities and resources
    1. Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
    2. What resources (for example financial and time) will be dedicated to data management and ensuring that data will be FAIR (Findable, Accessible, Interoperable, Re-usable)?

The guidance document further describes the selection criteria of a data repository and the development of a DMP template, which reflects the above outlined set of minimal requirements.

5 Additional Resources

The Data Life-Cycle Management (DLCM) project details requirements of DMPs for SNSF project proposals. They provides the corresponding SNSF DMP templates (pdf & docx), which was prepared jointly by teams from the libraries of EPFL and ETH Zurich, with input from DLCM partners.

Further resources can be freely downloaded and used:

DLCM SNSF DMP Template (pdf)

DLCM Data Management Checklist

DLCM Generic DMP Template

EAWAG DMP Guide

DMP Canvas Generator