Module 4: Open research data

After completing this module, you can…

Explain the benefits and challenges of sharing research data.
Recognize the principles and steps of data sharing.
Describe the significance of data management planning in the context of data sharing.
Acknowledge the importance of metadata and the FAIR principles, and why they help others to understand and reuse your data.

What are research data?

Research data are often the most valuable output of research projects. Research data can be described as any information that has been collected, observed, generated or created to validate original research findings.

Research data can include (Fig. 11):

Fig. 11. Research data can be just about anything.

The best practical recommendation for research data is to be as open and FAIR (Findable, Accessible, Interoperable, Reusable; see Making it FAIR) as possible, while acknowledging the ethical, commercial and privacy constraints with sensitive and proprietary data. It is also worth pointing out that currently more and more research funders expect the data produced in the research projects they finance to be findable, accessible and as open as possible.

Degrees of openness

The degrees of openness may vary from data that is freely available for everyone to strictly confidential data that only certain researchers can access. Data can also be shared with a specific group (e.g. research group) or for certain purposes, such as for research or educational purposes.

Open research data

Sharing data with restrictions

Closed data

Research data may include sensitive information, such as personal data, sensitive personal data, sensitive species data related to endangered animals and plants, or otherwise confidential data related e.g. to patents, national defence or trade secrets. In these cases, it must be carefully considered whether it is possible to share the data and what procedures it requires. Highly sensitive data, such as special categories of personal data, or otherwise confidential data, may not be possible to share at all (closed data). Protection of the identity of human participants is a common reason for closed access, and usually only anonymous data can be shared. However, even if the actual data can’t be shared, the metadata describing the research data can often still be made available.

Ideally, open data have no restrictions on reuse or redistribution, and they are appropriately licensed. Sharing exposes data to inspection, forming the basis for research verification and reproducibility, and opens a pathway to a wider collaboration.

Making research data openly available for others:

Improves the extensive usability and reuse of the research results.
Advances research, and enables new observations and phenomena to be discovered.
Provides researchers equal opportunities to utilise research data.
Reduces the need for duplicative efforts.
Allows the aggregation of multiple datasets, enabling more comprehensive meta-analyses and systematic reviews.
Promotes research collaboration.
Enables students to use real-world data to enhance their analytical and methodological skills.

For a researcher, opening the data is a scientific merit. Achievements in producing and sharing research data count as a scientific and societal impact in research work. Sharing data is worth adding to your CV (see e.g. the Research Council of Finland: CV Guidelines, Scientific and societal impact). Opening the data merits a researcher via citations to open research data and publications produced from the data.

Remember:

Research data can be just about anything that researchers work with and on which their research findings are based on.
The degrees of openness may vary from data that is freely available for everyone to that which is strictly confidential.

Updated: 8/2025

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