Guidelines on FAIR Data Management

As open as possible, as closed as necessary

This is a synopsis of these guidelines. The full document is available here.

The Open Access Research Data Pilot (ORD) was run over selected areas of Horizon 2020 between 2014-2016. Under the 2017 work programme it has now been extended to cover all thematic areas.

The Commission acknowledges that there may be good reasons why data cannot be made available so there are opt-out possibilities at any stage: the grant application stage, during the grant agreement preparation phase and after the signature of the grant applications.

Costs associated with open access to research data can be claimed as eligible costs of the any H2020 grant.

Data Management Plans (DMP)

DMPs are an essential part of good data management. A DMP should cover

  • The handling of research data during and after the end of the project.
  • What data will be collected, processed and/or generated.
  • Which methodology and standards are used.
  • Whether the data will shared/made open access.
  • How data will be curated and preserved (including after the project).

Proposal, Evaluation and Submission

The application should state what standards will be applied, how the data will be exploited and/or shared/made open access for verification and reuse, how will the data be curated and preserved. If the data will not be made available, this must be justified. The proposal should include resourcing and budgetary planning for data management and include a deliverable of a DMP at month 6 of the proposal.

Once the project has started a first version of the DMP must be delivered within 6 months. The DMP must be updated during the course of the project if there are significant changes. The DMP should be updated in conjunction with periodic reviews/evaluations and definitely for the final review.

Costs related to open access to research data in H2020 are eligible for reimbursement during the duration of the project under the conditions defined in the Grant Agreement (Article 6 and Article 6.2.D.3) but also other articles relevant for the cost category chosen.


FAIR Data Management at a glance: issues to cover in your Horizon 2020 DMP

Data summary 

  • State the purpose of the data collection/generation.
  • Explain the relation to the objectives of the project.
  • Specify the types and formats of data generated/collected.
  • Specify if existing data is being re-used (if any).
  • Specify the origin of the data.
  • State the expected size of the data (if known).
  • Outline the data utility: to whom will it be useful.

Making data findable, including provisions for metadata

  • Outline the discoverability of data (metadata provision).
  • Outline the identifiability of data and refer to standard identification mechanism. Do you make use of persistent and unique identifiers such as Digital Object Identifiers?
  • Outline naming conventions used.
  • Outline the approach towards search keywords.
  • Outline the approach for clear versioning.
  • Specify standards for metadata creation (if any). If there are no standards in your discipline describe what type of metadata will be created and how.

Making data openly accessible

  • Specify which data will be made openly available? If some data is kept closed provide the rationale for doing so.
  • Specify how the data will be made available.
  • Specify what methods or software tools are needed to access the data. Is documentation about the software needed to access the data included? Is it possible to include the relevant software (e.g. in open source code)?
  • Specify where the data and associated metadata, documentation and code are deposited.
  • Specify how access will be provided in case there are any restrictions.


Making data interoperable

  • Assess the interoperability of your data. Specify what data and metadata vocabularies, standards or methodologies you will follow to facilitate interoperability.
  • Specify whether you will be using standard vocabulary for all data types present in your data set, to allow inter-disciplinary interoperability? If not, will you provide mapping to more commonly used ontologies?


Increase data re-use (through clarifying licences)

  • Specify how the data will be licenced to permit the widest reuse possible.
  • Specify when the data will be made available for re-use. If applicable, specify why and for what period a data embargo is needed.
  • Specify whether the data produced and/or used in the project is useable by third parties, in particular after the end of the project? If the re-use of some data is restricted, explain why.
  • Describe data quality assurance processes.
  • Specify the length of time for which the data will remain re-usable.

Allocation of resources

  • Estimate the costs for making your data FAIR. Describe how you intend to cover these costs.
  • Clearly identify responsibilities for data management in your project.
  • Describe costs and potential value of long term preservation.


Data security

  • Address data recovery as well as secure storage and transfer of sensitive data.


Ethical aspects

  • To be covered in the context of the ethics review, ethics section of DoA and ethics deliverables. Include references and related technical aspects if not covered by the former.


Refer to other national/funder/sectorial/departmental procedures for data management that you are using (if any).


More information about data management is available here

Please note that data can be deposited in

A good description of the rational and operation of the pilot scheme is to be found in

Guedj, R. & Ramjoué, C. European Commission Policy on Open-Access to Scientific Publications and Research Data in Horizon 2020. Biomed Data J., 2015, 1(1), pp.11-14. Doi: http://dx.doi. bmdj.01102org/10.11610/

Useful links

Guidelines on Data Management in Horizon 2020

How to Create a DMP Plan/Open Research Data Pilot-OpenAIRE

Digital Curation Centre Online DMP tool

Metadata Standards Directory


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