A good DMP ensures that the management of data is secure, justifiable and in accordance with effective regulations and agreements. It also contributes to making the data FAIR.
Most research funders (including INN University) demand an overarching DMP as part of the project application, and for a more detailed plan to be created at the start of the project.
DMP contents
The DMP must describe how the data is managed during the whole cycle of research data, and it is strongly connected to the research design of your project. View the plan as a methodology chapter, where you similarly describe the process of managing data as conducting research.
Checklist for DMP
There are multiple examples of checklists for what makes a good DMP. Here are the most central aspects that you should consider and explain:
Research method
What types of data do you need to collect in order to answer your research question? E.g. questionnaire and numbers in quantitative studies, or sound and text in qualitative.
Consider the target audience and ethical concerns
- Who are you collecting data from? The target audience may influence what type of data you may collect. E.g. from children or vulnerable groups.
- All research projects must comply with ethical guidelines. This may limit what type of data you may collect. Do you need informed consents from participants before collecting data?
- Applications for Sikt data protection services, REK (ethical committee) and other approvals must be in place before you start collecting data.
- Describe the considerations and initiatives done to ensure that your project is ethical.
- Set procedures early so that the informants can exercise their rights under the GDPR, such as the right to access their data, or the right to have their data deleted. Here is information concerning the use of electronic consent.
Plan the data collection, storage and analysis
- Identify what type of data that you are collecting (green, yellow, red or black), and what security level and confidentiality classes these fall beneath. See information here.
- Describe how you will collect the data (e.g. questionnaires, interviews, statistics from databases).
- Describe how you will ensure that the data you collect are precise and of high quality. Is there need for a validation process?
- Describe where the data will be stored during the project
- What software or research platform (TSD/Educloud) do you intend to use? See list of approved software by INN University for collecting research data.
- NB! Is there a need for new software? Read about the acquisition process here (only for INN University staff).
- In what format will de data be stored? Choosing a format that is compatible with the analysis tools you plan on using may save you time. Also consider that the formats should be open, and not proprietary, to keep the data as FAIR as possible.
- Describe the methods you will use for data analysis.
Data organisation
- Establish a systematic approach for cataloguing and organising your data.
- Implement a file name system that makes it easy to identify and rediscover data.
A film for inspiration. - Describe the contents of your files with metadata, e.g. in a README file (here is a template).
- Decide and describe who will have access to your data and implement control measures for access. There must be a person responsible for assigning and removing access for the users of the data, and to keep the DMP updated.
- Ensure that all project participants are familiar with the method for data management.
Filing and sharing of data
- Decide what data that shall be filed at the end of the project – as openly as possible, as closed ad necessary.
- The archive of the university is called DataverseNO.
- Decide under what criteria the data are to be shared, e.g. the license Creative Commons. See relevant licenses here.
- Ensure that the methods for sharing data are secure and adhere to the data protection requirements. Be extra cautious if the data need to be anonymised before filing.
Storage and destruction of data
- Decide how long the data should be stored. (Be aware of what information you include in the consent form about this, so that you do not prevent filing and sharing/reuse of the data at a later time.)
- Make a time schedule for the destruction of data after the storage period.
- Ensure that the methods of destruction are secure and in compliance with the GDPR and other regulations.
Tips for calculating costs and working hours
Set aside work hours and time to:
- Develop and revise the DMP
- Create agreement forms concerning the responsibility of and access to data, especially in collaboration projects.
- Apply for and wait for approvals from Sikt data protection services, REK (regional ethical committee) and/or Inn University (local ethical committee).
- Do training in data management.
- Clarify the access and license of different IT systems.
Estimate costs for:
- Time for planning (X hours).
- Licenses/accesses for, and potentially the purchasing of, IT systems that are not open and commonly available
- Hours per week or the work percentage for the data steward during the whole project period.
Examples of DMPs
There are numerous programs that can aid you to make a DMP. Most of them are free of charge for single users/single projects. According to a project report by UB-BOTT in 2022, the most suitable online services for making a DMP are the following:
- DMPonline is often recommended for EU-financed projects as this tool has its own templates and works well for most plans. DMPonline is developed by Digital Curation Centre. NB! Note that when adding you institution in the registration process, you must put “other” as INN University does not have its own institutional user (you find “other” in the drop-down menu).
- Sikt DMP is a Norwegian DMP tool. This is recommended for projects that are in touch with Sikt regarding data protection, and/or that are receiving approval from REK as the tool is integrated directly with the registration form. It also has an embedded confidentiality classification for data.
- Data Stewardship Wizard (ELIXIR NO) is a comprehensive tool, with many integrations with other services, where the goal is to make machine-readable DMPs. Here you will also find templates for data plans made by the Norwegian Research Data Alliance in 2024.
- EasyDMP is a tool made by Sigma2 (a company connected to Sikt) and is largely based on free text.
- The DMP template by INN University in the project portal may be used, and this is a Norwegian version of the EU-Horizon template.
You can also find tips in RDMkit, developed by the EU project Elixir Converge.
The FAIR principles
The overarching goal of the FAIR principles is to make data from finished research projects “Findable, Accessible, Interoperable and Reusable.” This basically means that the data material should be easy for others to find, understand and use.
Guidelines for classification and storage
The types of data that are collected in your projects decide what Inn University research platforms you must use to ensure that the data management is In compliance with regulations and guidelines. Read more about software for data collection, storage requirements, tools for analysis and filing.
The detail level of the DMP
Inn University as an institution is responsible for research data being managed correctly, but it is the project manager who must ensure that the requirements are met. There is no set guideline for how detailed the DMP should be, but a rule of thumb is that the descriptions should cover enough to decide whether the project meets the requirements of information security, ethics, data protection, intellectual property rights (IPR) and FAIR data.
Useful contents
- Guidelines for research data at INN University
- Data protection in research
- Research ethics
- Intellectual property rights (IPR)
Contact information
- endre.aas@inn.no
- Phone
- +47 62 43 04 20