Case Statements




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The Exposing DMPs WG group is being retired. To participate in current RDA effort on Data Management Plans, please join the Active DMPs IG.


The Exposing DMPs draft recommendations respond to growing interest in exposing data management plan content to other actors (human/machine) in the research lifecycle. By 'exposing' we mean sharing with stakeholders other than the DMP author, funding body and institutional staff who would normally have access to information on a research project or proposal. Our working group sought to identify effective, efficient and ethical practice in this area. 

There is potential value in exposing plans for a variety of the stakeholders involved in their production and consumption. These stakeholders will benefit significantly from adoption of the recommendations, which address shared interests in using Data Management Plans to demonstrate that research products have been managed according to research community standards and generic principles (e.g. that the research products should be FAIR), and in giving recognition to researchers and others for their efforts in making this happen. 



A standard for expression and interchange of DMPs is available from the DMP Common Standard Working Group

Within this context we aimed to better understand user needs, and the benefits and risks to stakeholders of different modes of action. The working group has run a survey,  conducted interviews, convened plenary session discussions, and run polls to inform our draft recommendations. This work has surfaced the following main themes:

  1. Benefits from sharing exemplars to help learn data management planning, and from the better availability of information about data management costs
  2. Risks of sharing sensitive information from the DMP, concerns about scooping and about changes to plans being perceived negatively
  3. Applying FAIR principles to DMPs. This may be to improve DMPS as tools for making research outputs FAIR. Or to aid transparency, by making DMPs FAIR as records of planning and execution.
  4. The need for DMPs to be machine-actionable, to enable their integration into the research workflow, and interoperability with institutional or external systems and services


Methods used

The first step involved analysing the DMP Common Standards User Stories. This analysis resulted in eight Use Cases.


Use Cases

  1. Deposition: Submit DMP to a repository or registry

  2. Estimation: Mine individual or collected plans for requirements planning

  3. Evaluation: Review DMP for completeness and policy alignment

  4. Integration: Integrate DMP in research workflows

  5. Notification: To notify services of anticipated resource and support needs

  6. Publication: Publish DMP for research visibility

  7. Resourcing: Costing the planned data management activities

  8. Transparency: Ability to see (updated) record of output which describes management intentions and actions

The Use Cases above  informed the design of the survey instrument.



Qualtrics Survey Software was used to develop and administer the survey. The survey was distributed in April 2019 via various channels available to the co-chairs, e.g. DMPOnline users, DMPTool users, coordination fora such as CODATA, French Committee for Open Science, Swiss DLCM. 

The key beneficiaries of the WG assessment are stakeholders with a common interest in using Data or Software Management Plans as instruments for demonstrating that research products have been managed according to research community standards and generic principles (e.g. that the research products should be FAIR), and that recognition is given for doing so. There were 571 responses: 409 complete, 42 at 52% complete and 120 at 13% complete. 

The data were de-identified and uploaded to the RDA Exposing DMPs file repository - and the results data is visualized online. The survey instrument is available at: The assessment indicates there is value in exposing plans for a variety of stakeholders involved in their production and consumption. These include researchers themselves, funders, institutions, and a variety of service providers and community organisations including repositories, institutions, journals, publishers, and providers of tools to help write and maintain plans.



The Survey underpinned a nymber of interviews that followed. Stakeholders interviewed included funders, service providers, institutions and repositories. These interviews have further refined our understanding of the landscape and why, how, when and where DMPs can or should be shared. Note * the main focus was on Data Management Plans (DMPs) but we sought examples of Software Management Plans (SMPs) where relevant to the exposure use cases of interest to the Active DMP Interest Group.   Through consultation with users of well-established planning tools (DMPTool, DMPonline), the Use Cases Catalogue was intended to identify the degree of acceptance among researchers for the levels of exposure/publication each use case entails, barriers to realising the benefits, and any concerns about undesirable impacts.


Plenary Input

Importantly, one of the major information collection and feedback points has been successive plenaries, starting at Plenary 11 in Berlin through to Plenary 15 in Melbourne. A Mentimeter poll run at Plenary 14 in Helsinki provided the working group with a prioritised list of themes for recommendations.


Potential benefits identified

  • mutual learning about data management practice
  • feedback on planning for FAIR research outputs, including cost estimation
  • better quality of data management if some tasks are automatized, distributed and taken in charge by relevant experts
  • planning opportunities for repository managers (in terms of resources required, timing, and ability to advise researchers on best practices before the data are collected)
  • opportunities for funders to compare DMPs with datasets deposited on project completion

Potential risks identified

  • getting scooped on active research
  • disclosing information to enable re-identification of personal data
  • disclosing confidential or sensitive data 
  • impacting data security (if data transfer or storage security measures exposed)
  • picking up/following bad data management practice if DMP quality not sufficient
  • researcher perception that DMPs are a burdensome administrative obligation


Implementing Effective DMP Practices

The Exposing WG also set out to develop a Use Cases Catalogue to describe implementation scenarios and articulate their benefits to researchers and other stakeholders, with case studies of how those benefits have been realised. This work was incomplete due to COVID-19 interruption. However the WG co-chairs were involved in US and European initiatives influenced by the draft recommendations. 

These initiatives include the 2020 Report, Implementing Effective Data Practices: Stakeholder Recommendations for Collaborative Research Support  at This report makes suggestions for improving research data sharing and infrastructure in ways that are aligned with the findings of this working group.  The report is intended to encourage collaboration and conversation among a wide range of stakeholder groups in the research enterprise by showcasing how collaborative processes help with implementing PIDs and machine-actionable DMPs (maDMPs) in ways that can advance public access to research.

Five key takeaways from the report are:

  1. Center the researcher by providing tools, education, and services that are built around data management practices that accommodate the scholarly workflow.
  2. Create closer integration of library and scientific communities, including researchers, institutional offices of research, research computing, and disciplinary repositories.
  3. Provide sustaining support for the open PID infrastructure that is a core community asset and essential piece of scholarly infrastructure. Beyond adoption and use of PIDs, organizations that sustain identifier registries need the support of the research community.
  4. Unbundle the DMP, because the DMP as currently understood may be overloaded with too many expectations (for example, simultaneously a tool within the lab, among campus resource units, and with repositories and funding agencies). Unbundling may allow for different parts of a DMP to serve distinct and specific purposes.
  5. Unlock discovery by connecting PIDs across repositories to assemble diverse data to answer new questions, advance scholarship, and accelerate adoption by researchers.

In the European context the EC funded project FAIRsFAIR produced FAIR practice recommendations. Informed by the Exposing DMP WG recommendations, these proposed that stakeholders should:

  1. Formalise and support appropriate data management plans (DMPs) for FAIR data. This recommendation called on Research communities, with support from data stewards, to agree templates for DMPs that identify useful steps towards making data FAIR in a domain-relevant way. It also advised that Researchers, data stewards and academic journals should use FAIR data criteria to review whether a DMP includes appropriate steps to make the data FAIR.
  2. Develop roadmaps, guidance and workflows for machine-actionable data management plans. This recommendation called on DMP platform providers, institutions, repositories and other data service providers to adopt the RDA Common Standard for Machine-Actionable Data Management. It also proposed that Institutions and research communities should prepare a roadmap and guidance for implementing machine-actionable DMP workflows.

To accompany these recommendations 3 relevant case studies were included in the ‘implementation stories’ section of the FAIRsFAIR website.

The WG aimed to produce a Reference Model to document generic components and workflows for exposing plans (and metadata about them), and offer recommendations for further action by each of the relevant stakeholder groups. Much of this community endorsed advancement is now being undertaken within the context of the Active DMPs IG and interested persons are encouraged to join.