Rec. 12: Data Management via DMPs

[sjDCC]

Any research project should include data management as a core element necessary for the delivery of its scientific objectives, addressing this in a Data Management Plan. The DMP should be regularly updated to provide a hub of information on the FAIR data objects.

• Research communities should be required and supported to consider data management and sharing as part of all research activities.
  Stakeholders: Funders; Institutions; Data stewards; Publishers; Research communities.

• Data Management Plans should be living documents that are implemented throughout the project. A lightweight data management and curation statement should be assessed at project proposal stage, including information on costs and the track record in FAIR. A sufficiently detailed DMP should be developed at project inception. Project end reports should include reporting against the DMP.
  Stakeholders: Funders; Institutions; Data stewards; Research communities.

• Research institutions and research projects need to take data management seriously and provide sufficient resources to implement the actions required in DMPs.
  Stakeholders: Institutions; Data stewards; Research communities.

• Research communities should be inspired and empowered to provide input to the disciplinary aspects of DMPs and thereby to agree model approaches, exemplars and rubrics that help to embed FAIR data practices in different settings.
  Stakeholders: Data services; data stewards; Research communities.

[hollydawnmurray]

F1000 position: We would encourage that DMPS be called OMPs (‘output management plan’), to be more holisitic and inclusive of a variety of output types and not only what is traditionally viewed as data. This terminology is already in use, for instance in the OPSSPP recommendations and by the Wellcome Trust. This would help to highlight the FAIRNESS of other objects like code, materials, etc. which (aside from Rec 3) are not fully fleshed out here.

An action that seems to be missing is: how will DMPs be incentivised? This is touched upon broadly in Rec 14, but it would be wise to incentivise this practise directly given the effort that will be required by researchers. This recommendation also relies heavily on groundwork being set by Rec 26, which raises the question of time scales: when will the DMP requirement be implemented? Does this allow enough time for necessary education and training of researchers prior to implementation?

[katerbow]

DFG position: DFG supports the use of DMPs for scientific projects since DMPs help to manage data in a structured manner throughout the lifetime of the projects. However, DMPs have to be considered as a supporting tool or method and not as a primary mean for quality evaluation of the project. Depending on the discipline specific status of the data-sharing culture and availability of appropriate disciplinary policies, the type of a DMP may vary significantly and may not be able to follow a standard scheme. The central purpose of such plan should be to achieve reusable data-output following given and approved standards.

Developing and writing those plans should receive professional support by information specialists and should not lead to an inadequate workload for scientists.

[ronzino]

PIN position: We fully agree with considering data management as a core part of the research process, via regularly updated and submitted DMP. Data Management Plan templates should be tailored to the needs of specific disciplines and research communities, involving them in the development of targeted models in order to make it a common practice among researchers.
This may act as an incentive to encourage researchers to consider data management in their research activities.
We are currently making such an effort in the framework of the PARTHENOS project, by creating a DMP template specifically designed for the archaeological community. The model provides a guide for the compilation of all fields, with a list of recommended answers, and pointing to the relevant standards, facilitating in this way the compilation of the DMP, helping people to understand the questions and offering them alternatives.

[ScienceEurope]

Science Europe is currently working on the alignment on Core Requirements for DMPs among funders in Europe. This endeavour is undertaken in coordination with the EC and other relevant stakeholders. Many of the points mentioned in Rec. 12 have been taken care of in these Core Requirements which will be published by the end of 2018.

[ferag]

I would add in " The DMP should be regularly updated to provide a hub of information on the FAIR data objects" that that update should be automatic whenever possible exploiting the potential machine-actionability features of DMPs

[RCN2018]

• How should DMPs be assessed? Who should assess them?
• Could assessment be part of DMP-tools (like DMP online or other tools)?
• Other point to consider: DMPs should be made publicly accessible for mutual learning
• Data Management Plans (DMPs) are recognized as important. However, different requirements for DMPs at different levels (institutional, national and international) should be avoided since researchers are not happy to submit more than one DMP for the same data for their different affiliations, project funders, repositories etc.. Therefore harmonization and sharing of DMPs should be a priority.

[pkdoorn]

Thumbs up. Two refinements:

• Stimulate the harmonization of DMP requirements across research funders, universities and other research organisations.
• Stimulate the formulation of Domain Protocols for data management by research domains/disciplines/communities, like proposed by Science Europe.

[mromanie]

ESO position
We have implemented DMPs and find them a very useful tool to monitor the progress of a project wrt agreed and understood specifications.

[carrd]

Wellcome Trust position:
To echo/expand on the comment from F1000 above, Wellcome now requires Outputs Management Plans as opposed to Data Management Plans - explicitly including software and materials alongside data as valued research outputs. We were really pleased that the report (p39) recognised that DMPs should cover these other outputs, but think this needs to be made explicit in the recommendations (if it was then I missed it). I agree with the comment above that assessment of DMPs (responsibility and criteria) might be an area in which further cross-funder consensus/alignment might be valuable.

[npch]

SSI position:

We endorse F1000’s and Wellcome Trust's comments, and also call out the need for these OMPs to be machine readable/actionable. We believe that domain-specific templates should be encouraged that build upon a common core. This allows for coordination and harmony between top-down and bottom-up approaches to specifying useful and used DMPs/OMPs.

[perrin1024]

ILL Position: We support this proposal. We should also find a way for the RIs to automatically provide/integrate/link information in existing DMPs where data produced at the RI are used.

[gtoneill]

Fully support the implementation and use of DMPs in research projects. It is crucial that there are somewhat standardised DMP templates available for researchers to use and that researchers are adequately trained and supported in FAIR Data and the use of DMPs. Data stewards will likely play a prominent role in this training and support and thus themselves need to be adequately trained in FAIR Data and DMPs as well as be employed timely in adequate numbers at institutions. DMPs should be required to be submitted in all research applications albeit in a preliminary and outlook form. The DMPs can be developed during the project and should serve as both a guideline and for assessment.