Open Research data
The University Library offers guidance on various aspects of research data planning and management.
Most major research funders require projects to archive and make available research data. Many publishers also require authors to make the data underlying the findings described in their publications available.
Research data archiving
Many data archives fulfil the requirements from funders. Researchers at UiB can archive data in UiB Open Research Data.
It is also possible to store your date outside UiB. Some projects funded by the Norwegian Research Council, are required to archive their data with NSD. There are also many international subject specific archives. The webpage re3data.org is the largest and most comprehensive registry of data repositories available on the web.
Sensitive personal data
Projects that collects personal data must consider if the project should notify NSD. Read more. The IT-department at UiB has a service for secure storage and access to sensitive data, SAFE (Information in Norwegian).
The Norwegian Research Council and Horizon 2020 require projects to submit a data management plan (DMP). A DMP describes how data will be collected, processed and made available during the lifetime of the project and after the project has ended. A DMP should also describe how sensitive data are managed.
There are several different tools for creating data management plans. By using these tools you have the opportunity to create DMPs in accordance with requirements from different research funders. You can also share the DMP and others can edit it. Examples of tools are:
The advantage of NSD is that you get advice on chat or email and the tool is integrated with Cristin, thus you avoid double registration. DMPonline and DMPTool provides examples of public data management plans.
Frequently Asked Questions (FAQ)
What is research data?
In general, research data can be defined as all data which are created by researchers in the course of their work.
Information, in particular facts or numbers, collected or created to develop claims made in the academic literature, e.g. statistics, results of experiments, measurements, observations resulting from fieldwork, survey results, interview recordings, images etc.
What are the FAIR principles?
Where can I find existing research data?
In the article "Eleven quick tips for finding research data" Kathleen Gregory and her colleagues (2018) share some useful tips to find and reuse existing research data. See also the video below made by Utrecht University.
What is metadata?
Metadata is structured information that describes, explains, locates, and makes it easier to retrieve and use an information resource.
In order to help make your data reusable and accessible to you and others in the future, you need to create and archive accurate metadata along with your data. Discipline-specific examples of metadata are provided by the Digital Curation Centre, and can be found here: http://www.dcc.ac.uk/resources/metadata-standards
Do I need to upload all my research data from my research project?
No, you need to go through a selection process in order to make a decision on which data do you need to keep; which data do you wish to keep; which data shouldn’t be kept or isn’t worth keeping; what are the retention periods from my funder, the university, and any legal or regulatory requirements.
Where no specific guidance is available, we recommend researchers keep in mind two things when deciding which data to share:
- What data are necessary to reproduce or validate your results? Note that this may include code.
- What data have the potential for reuse by others?
The Digital Curation Centre (DCC) has some useful guidance ‘Five steps to decide what data to keep’.
Are there any "best practices" for managing research data?
The following are some of the components necessary for good data management practices.
- Use descriptive and informative file names
- Choose file formats that will ensure long-term access
- Track different versions of your documents
- Create metadata for every experiment or analysis you run.
See the Deposit Guide of UiB Open Research Data or DataONE Best Practices Primer for more information.
What formats are best for preserving files in the long term?
Commonly used formats such as those produced by Microsoft Office products (e.g. Word documents or Excel spreadsheets) are very likely to have reasonable longevity, but be aware that they are proprietary (owned by someone) and so will not necessarily exist forever or remain easily readable.
Instead you should use open, non-proprietary formats – for example, txt. rather than Microsoft Word, CSV rather than Excel, TIFF rather than Photoshop files, or as XML rather than a database. For more examples, see
However, open formats may not support all the functionality found within a proprietary format, or they might result in larger files because they offer less efficient compression of files. Sometimes, you will want to store your data in its original format and also in a more open or accessible format for sharing, archiving, or future use. For more information on preferred file formats, see here.
What are 'non-proprietary' or 'open' formats, and why should I use them?
A non-properitary format is a format which does not have restrictions on its use and over which no one claims intellectual property rights. For example, Microsoft Office products, such as Microsoft Word, are proprietary, while Open Office products are non-proprietary (and open source).
For long term access to files, digital preservation experts tend to recommend 'non-proprietary' and 'open' formats. The logic here is that if the code behind the software is publically available (i.e. open source), then that format/software will be supported so long as at least one competent tinkerer still finds it interesting or useful. In contrast, a private software company can go out of business or stop producing a compatible version of the software in whose format your data was saved, and no one will have the rights or knowledge to provide it anymore.
What is a data management plan?
A data management plan describes how data will be managed during a research project and after project completion. The purpose of a data management plan is to evaluate different aspects of the handling and managing of research data, from data collection/generation, processing, analyses, documentation, storage and data sharing. See DMP_checklist for more information.