Research Data Management Plan

Research data management (RDM) is a process in the research lifecycle that includes the creation (collection or acquisition) of research data, their organisation, digital stewardship, storage, (long-term) preservation, security, quality assurance, allocation of persistent identifiers, providing metadata, issuing appropriate licenses and procedures for data exchange, sharing and reuse.

Research data management must be accurately planned in advance with the help of a research data management plan (RDMP). Research data management plans are the basis of responsible data management and became mandatory in 2021 for the Horizon Europe and European Research Council (ERC) projects, regardless of whether data is created or reused. Beneficiaries must submit them within the contractual period, which is usually 6 months from the signing of the contract.

You can create research data management plans yourself or use templates that are often suggested by funders or institutions. Typically, the plan consists of questions that you answer in a way that is consistent with the goals and expected way of conducting the research. The form of the plan largely depends on the research itself. The plan is also a living document that can be updated and supplemented as the project progresses. Changes may relate to newly generated data or to the originally planned activities. For projects longer than 12 months, updating is mandatory, both during the project and at the end, when the plan needs to be adapted to the actual situation.

The recommended practice is to open and publish plans on appropriate platforms, such as Research Ideas and Outcomes (RIO) Journal, or in dedicated repositories, such as DMP Online. You can also find many examples of good practices for creating research data management plans on both platforms.

Essential Contents of a Research Data Management Plan

A research data management plan must contain the following essential information:

1. Description of Data

A precise description of the generated or reused data, including the content aspect, data type and data volume assessment, is crucial for interoperability and reusability. The more precisely the data is described, the more efficient the interoperability and reuse will be.

2. Standards and Metadata

Protocols and standards used in data structuring (e.g., standard metadata schemas) are also very important for ensuring interoperability and reuse. It is recommended to use standards that are recognized in the individual research field.

3. Persistent Identifiers

The RDM plan must contain information about the type of persistent identifiers you will use. Most trustworthy repositories assign persistent identifiers when archiving data to the repository.

4. Digital Stewardship and Data Protection

The RDM plan must contain information on data quality assurance (link), data lifetime, permanent storage and data access, including information about the repository and assessment of whether the repository is trustworthy.

5. Data Sharing Terms

The RDM plan must provide detailed information about the conditions of data sharing, including the terms of use and the license under which the data is accessible and can be reused.

6. Management of Other Research Results

For effective interoperability and reuse, it is necessary to provide information on how other research results (e.g., software) will be accessible. It is imperative that other results are also accessible according to FAIR principles. The information should include a detailed description of individual results, relevant metadata standards, persistent identifiers and archiving, digital stewardship and permanent storage.

7. Data Management Costs

Often, data management costs are a legitimate cost under the contract with the funder of the research work, but it is essential to note the cost estimate (e.g., data creation costs, documentation costs, storage costs, repository costs, data quality assurance costs, RDM staff costs) also in the RDM plan.

The structure of many research data management plans (e.g. for Horizon Europe and ERC projects) is designed to enable the FAIRification of data already before their creation. However, if you are preparing a management plan for existing data, you can use the FAIR Self Assessment Tool check to what extent they meet the FAIR principles and what needs to be improved.

Research Data Management Plan Templates

Some current proposals for research data management plans prepared by funders and other institutions can be found at the links below:

• Horizon Europe Data Management Plan Template
• ERC Data Management Plan Template
• Prepare a Data Management Plan. A Set of Questions From the »Data Management Expert Guide« Online Textbook (adapted from the Data Management Expert Guide of the CESSDA consortium, recommended by the Social Science Data Archives)
• Recommendations for a computer code management plan (Software Sustainability Institute)

Since many research data management plans are very complex, especially those for Horizon Europe projects, CTK UL prepared an annotated template of this plan. We have added explanations to the basic template that will help you understand the plan and prepare answers to the questions asked. You can download the annotated template from the link below (it is currently only available in Slovenian).

Online Tools for Creating Research Data Management Plans

Creating a research data management plan is even easier with the help of some online tools that already contain proposals from different funders. The advantage of online tools is also the easy sharing of files with other members of the research group or project consortium and joint editing of documents. Here we will highlight the three most widely used tools.

The DMP Online is the oldest online tool for creating research data management plans. It was founded in 2010 as a joint project of the UK Digital Curation Center and California Digital Library. The templates are mainly adapted to the requirements of the European Commission and European funding agencies, but some other templates can also be found, e.g., by the American National Science Foundation. The DMP Online website also serves as a repository of publicly available plans opened by other researchers. Use is free of charge.

The DMP Tool, modeled after DMP Online, was developed by the Data Observation Network on Earth (Data ONE) in 2011. The templates are adapted mainly to the requirements of American funding agencies and research institutions. It also offers the possibility of identifying the costs that will be incurred during the process of research data management, as well as planning financial resources in advance. Like DMP Online, DMP Tool serves as a repository of publicly available plans deposited by other researchers. Use is free of charge.

The Data Stewardship Wizard is a multi-functional online tool that offers fewer pre-made templates for research data stewardship plans than DMP Online and DMP Tool, but offers more flexibility in creating your own custom plan. In addition, it offers advice on data FAIRification and structuring the plan in a machine-readable format, integration with third-party tools and services, and estimating data storage costs. Data Stewardship Wizard is the result of cooperation between the Czech and Dutch nodes of the Elixir consortium, the Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, the Faculty of Information Technology of the Czech Technical University in Prague and the Dutch Technology Center for Life Sciences. The first official version went live in 2016. Use is free of charge.

Argos is an open platform for creating research data management plans developed by OpenAIRE in 2020. It is based on the OpenDMP open source software and is available through the catalogues of OpenAIRE and European Open Science Cloud (EOSC) services. It contains guides that familiarise users with the basic concepts of research data management and guide them through the entire process of preparing a DMP. Argos also uses OpenAIRE's collection of services and related resources that make DMPs more user-friendly and easier to publish. The resulting plans are machine actionable, compatible with various information infrastructures and directly connected to the Zenodo repository. In Argos, DMPs are treated as research results that can be equipped with permanent identifiers and licenses and shared according to FAIR principles. Use is free of charge.

DataWiz is an online tool for creating research data management plans developed by the German Leibniz Institute for Psychology Information, which is adapted to research in the field of psychology. It covers all research data management steps, from organisation and documentation of research projects, use of DMP templates (mainly German and EU), exporting pre-registration documents, versioning control, conversion of data into appropriate formats, integration with the SPSS statistical software, and exporting documents to the PsychArchives institutional repository. Use is free of charge.

Last update: 14 October 2022