Data management planning

"Give me six hours to chop down a tree and I will spend the first hour sharpening the axe."
- Abraham Lincoln

   Main points

Data management planning is the structured way of thinking about the research data you are going to collect. What type of research data will the research project produce? What format will you use? How will you store them and how can they be accessed? By thinking about these questions(1) at an early stage and documenting your answers you will avert future problems as a researcher. 


One of the ways to think about the data collecting process is by using a format: a data management plan (DMP). These formats come in a variety of shapes and sizes, depending on the research discipline, requirements from the research funder and local initiatives.  

A data management plan can be a separate document. It helps the researcher identify and list the risks with regard to management of research data during the entire research process. Because not everything is known from the outset it is recommended to treat the DMP as a "living document", which can be revised and detailed periodically as the project goes forward.

Nowadays, research funders often require that a data management plan is included in the project proposal. In that case the research proposal contains a data section or a DMP is included as an annex. For research funders the reason behind it is to promote open access to research data. In their opinion research data, produced in the context of a publicly funded research project, should be freely made available for reuse and verification. Cases of data manipulation and sloppy science emphasize the importance of access to the original data. A popular notion in this context is FAIR(a): in principle, research data should be Findable, Accessible, Interoperable, and Reusable.(b) 

In the video below, we have listed what a data management plan is, what its advantages are and an example will be given of a format and a completed DMP. 

RDNL-Video about the what, why and how of data management planning;
use HD quality for the best viewing experience.

The Digital Curation Centre’s Checklist(c) for a Data Management Plan provides a useful list of questions to consider when writing a DMP:
  • What data will you collect or create?
  • How will the data be collected or created?
  • What documentation and metadata will accompany the data?
  • How will you manage any ethical issues?
  • How will you manage copyright and intellectual property rights issues?
  • How will the data be stored and backed up during research?
  • How will you manage access and security?
  • Which data should be retained, shared, and/or preserved?
  • What is the long-term preservation plan for the dataset?
  • How will you share the data?
  • Are any restrictions on data sharing required?
  • Who will be responsible for data management?
  • What resources will you require to implement your plan?

     Cases involving requirements from research funders  

Below you will find some examples of research funders and their requirements with regard to a data management plan or a data section. The institutes usually supplies this information directly to the researchers, but data suporters can expect to be asked questions about it by researchers.

KNAW - Royal Netherlands Academy of Arts and Sciences

The Royal Netherlands Academy of Arts and Sciences (KNAW) states that(2) a data section has to be included in the research plan for each new research project started. 

The KNAW data section guide (Dutch)(3) specifies what a data section has to include. 


In addition, the KNAW produced a point of reference for a data notation (Dutch).(4) The document describes the institute-specific implementation of the KNAW open access policy and digital sustainability of research data. 

NWO - Netherlands Organization for Scientific Research

NWO, the largest research funding organization in the Netherlands, has tightened its policy regarding research data in 2011. Data deriving from research funded by NWO is co-owned(5) by it. For data files, both NWO and the knowledge institute that carried out the research are considered to be “producer of the database” as referred to in the Databases Act. This way the funder wants to encourage reuse of the research data.


One of the preconditions(6) for obtaining both a NWO Large or Medium subsidy within e.g. the Social and Behavioural Sciences programme is that a data contract(7) is closed when the research starts. In this contract agreements are made about the way the research data is to be archived and made available when the project has ended.

Wageningen University

From 1 April 2014, Wageningen University requires Chair groups and PhDs to have a data management plan available.(8)

Horizon 2020

Horizon 2020(9) the new European funding programme for research and innovation. With a proposed budget of 80 billion euros, Horizon 2020 should make it easier for researchers and institutes to get funding and to introduce new ideas to the market.

Horizon 2020 has a pilot for open access to research data. Participating projects are required to provide a data management plan that indicates what data will be open.


Also see 'Guidelines on data management in Horizon 2020'.(10)

National Science Foundation

Since 18 January 2011, The National Science Foundation (USA) requires(11) all research proposals to have an annex of no more than two pages titled 'Data Management Plan'.

  Cases with completed DMP's 

Below you will find a number of examples of completed data management plans:  

  • The DMP van het VIDI-project SPLITS (Splitting and Clustering Grammatical Information), awarded to Leiden University, Chair group Italian Language and Culture.(13)
  • A complete DMP by Lucie Vermeulen, PhD candidate at the Environmental Systems Analysis Group, Wageningen University.(14)
  • The data management plan by the Social and Organizational Psychology (SOP) department, Universiteit Utrecht.(15)
  • More examples through DCC(16) and Purdue.(17)

   An in-depth look 

    • There are various DMP tools to help a researcher prepare a data management plan by means of a 'webform': 
    • The SURF-project 'Regie in de cloud' (Cloud management) produced(22) data management recommendations.  

    • Purdue University’s Data Curation Profiles Toolkit(23) comprises data profiles of various fields of study. Data profiles are more comprehensive than a DMP:

      "A Data Curation Profile is essentially an outline of the 'story' of a data set or collection, describing its origin and lifecycle within a research project."

      The data profiels are collected in data interviews.(24)
       Examples of published profiles can be found here.(25)


Click to open/close
  1. Gesis. Research data management questions. Retrieved from
  2. KNAW. KNAW policy on open access and digital preservation. Retrieved from
  3. KNAW. (2011). Handvat voor het opstellen van een data paragraaf. Retrieved from
  4. KNAW. (2011). Handvat voor het opstellen van een data notitie. Retrieved from
  5. NWO. Regeling subsidieverlening. Retrieved from
  6. NWO. Investeringen NWO-middelgroot, maatschappij- en gedragswetenschappen. Retrieved from
  7. KNAW. Investeringen NWO-middelgroot, datacontract informatiefolder. Retrieved from
  8. Wageningen Universiteit. Data Management Plans. Retrieved from
  9. European Commission. Horizon 2020. Retrieved from
  10. European Commission. (2013). The EU Framework Programme for Research and Innovation. Horizon 2020. Guidelines on Data Management in Horizon 2020. Retrieved from
  11. National Science Foundation. Dissemination and Sharing of Research Results. NSF Data Sharing Policy. Retrieved from 
  12. n.v.t.
  13. Schoots, F.; Verhaar, P. (2011). Splitting and Clustering Grammatical Information (SPLITS). Data Management Plan. Retrieved from
  14. Vermeulen, L., (2013). Data management plan. Retrieved from
  15. Social and Organizational Psychology (SOP) department, Utrecht University. (2013, June). Data management plan of the Social and Organizational Psychology (SOP) department, Utrecht University. [draft version]. Retrieved from
  16. DCC. Data plan guidance and examples. Retrieved from
  17. Purdue University. Data Management Plan Examples. Retrieved from
  18. ICPSR. (2012). Guide to Social Science Data Preparation and Archiving. Retrieved from
  19. DANS Data Guide 8. (2010). Preparing data for sharing. Guide for social science data archiving. Retrieved from
  20. DCC, DMP Online. Retrieved from
  21. California Digital Library, DMP Tool. Retrieved from
  22. SURF, (2013), Rapport Ervaringen en aanbevelingen datamanagement (Regie in de cloud). Retrieved from
  23. Purdue University, Institute of Museum and Library Services, D2Cs, Data curation profiles toolkit. Retrieved from
  24. Witt, M.; Carlson, R. (2007). Conducting a data interview. [epub]. Retrieved from
  25. Data Curation Profiles Directory. Retrieved from
  1. Wilkinson, M.; e.a. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Retrieved from
  2. FORCE 11: FAIR principles. Retrieved from
  3. Digital Curation Centre’s Checklist. Retrieved from