Research data and Data Management Plans

A DMP is a dynamic document where researchers describe how research data should be managed throughout a research project. All projects awarded funding must assess the need for a data management plan.

The Research Council of Norway (RCN) describes Data Management Plans:

The plan is a living document that follows the research project and specifies the following:

• the kind of data that will be generated
• how the data will be described
• where the data will be stored
• whether and how the data can be shared

The purpose is to plan how to safeguard the research data, not just during the project period, but also for future reuse of the data. A data management plan is an effective means of identifying costs associated with data management and storage, and can also help you plan how to cover these costs.

We recommend using the Sikt Data Management Plan. It satisfies the requirements of the RCN and the European commission, and can be shared with colleagues in Norway and abroad. Alternatively the UiS word template can be used. This is for projects which does not handle personal data. This template is an adaptation of the UiT template".

Check out UiTs example overview of allready filled in Data Management Plans.

Feel free to contact Stavanger University Library if you are a researcher at UiS and need help with creating your Data Management Plan.

The reasons for making research data available, are twofold: it increases visibility and accountability. Research data forms the basis of scientific progress which is transmitted through journal articles, books or other publications.

By making your data available, you are enabling sharing and reuse. Other researchers can use existing data in their research.

You will often find that funders require you to create a DMP for publicly funded research, and that articles and data alike should be made openly available.

Researchers at UiS can use DataverseNO to archive their research data.

• Before you archive your data: make sure it is in line with the current guidelines. Learn how to prepare your data for archiving.

• Archive your data: When the data is ready for archiving, it should be submitted. Guide on how to submit it, or watch this video on how to submit research data in DataverseNO. We recommend that you fill in a few more fields in addition to the ones that are required. This will make your data set more accessible. Watch a video on how to do this.

In addition to DataverseNO, there are many other repositories for research data.

You should manage your research data according to the FAIR principles: Findable, Accessible, Interoperable and Re-usable. It’s about managing and describing data in a way that makes it possible for others to understand and use the data in the future.

This means that data and metadata should be machine accessible and machine readable. It also means that there needs to be persistent identifiers (such as a DOI), sufficient metadata, clear licences and use of accepted standards and formats.

It is important to be aware that only rarely will data be fully FAIR. The aim is to increase the potential for re-use, and in many cases, even small tweaks may increase the degree of FAIRness considerably. Additionally, keep the FAIR principles in mind even if the data is not made openly available, as the principles ensure good data management throughout the lifetime of the project.

These are some of the most widely used repositories and search engines for data searches:

• DataverseNo: repository with datasets from participating Norwegian institutions.

• The Research Council of Norway (RCN): Norwegian datasets.

• DataCite: Data Search Engine.

• Bielefeld Academic Search Engine: Search engine for research output. Select advanced search and limit your search to datasets.

• Google Dataset Search: Data Search Engine.

• Zenodo: Repository and search engine for research outputs. Perform a search and limit your results to datasets.

• Oria: Stavanger University Library's catalogue. Select advanced search and select “Research datasets" from Material type.

You can find an overview of data repositories from all over the world at re3data.