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Open Science

FAIRification

FAIRification of data and scientific practices helps guide researchers towards the paths they should – or should not – pursue. Without intuition, we are merely searching in the dark.

Open Science is now enshrined in Czech legislation

It is addressed by Act No. 328/2025 Coll., on Research, Development, Innovation and Knowledge Transfer.

 

Optional Open Science Practices

They become binding if project teams commit to them in the project documentation.

New Sanctions for False Information

False information provided to obtain bonus points in project evaluation is now subject to sanctions, particularly in relation to optional and mandatory Open Science practices.

A Data Management Plan Helps Prevent Sensitive Situations

It not only defines specific FAIRification procedures and measures for protecting patents and sensitive data, but also sets out procedures designed to protect researchers themselves.

Open Science & FAIR Data

Open Science is not merely a bureaucratic requirement. It is a way to accelerate the circulation of information, increase the credibility of research results and broaden the impact of scientific work. But does Open Science always mean the same thing as FAIR data – data that are Findable, Accessible, Interoperable and Reusable? And what exactly must researchers do in their projects to put Open Science into practice rather than fulfil it only “on paper”? You can find out in a short video prepared by Ing. Tomáš Heryán, Ph.D., Data Steward at CEET.

Open Science in Czech Legislation

Act No. 328/2025 Coll., on Research, Development, Innovation and Knowledge Transfer, PART FOUR, TITLE I: “Open Science” (§§ 82–83), requires FAIR research data to be made publicly available in institutional or thematic repositories in a machine-readable format under a CC BY licence (§ 83(3)). It also requires scientific publications published under a CC BY licence to be made available in repositories (§ 82(1)–(2)).

Optional Open Science Practices

Machine-readable electronic laboratory notebooks containing technical specifications of experiments and measurements can be linked to data storage systems as well as repositories. They improve research reproducibility and, through automation and standardisation, help reduce administrative burden.

Whenever estimates or conclusions are derived through computational methods, it is advisable to FAIRify the procedures used so that the results can be independently verified. Where AI platforms are used to analyse CC BY-licensed research data or publications, the exact prompts used may also be archived.

 For scientific publications, available Open Science practices may include the use of preprints hosted on publishers’ official platforms or open peer review. Another optional Open Science practice is citizen science, in which members of the non-academic public who contribute to the research process – for example through data collection, data analysis or preparation of a publication – are appropriately credited for their contribution.

Sanctions for False Information

A problematic situation may arise if we commit to optional Open Science practices in project documentation but subsequently fail to fulfil those commitments. This is also why Act No. 328/2025 Coll., on Research, Development, Innovation and Knowledge Transfer (§ 94(2)) introduces new sanctions for providing false information when seeking preferential project evaluation. Responsibility moreover lies with the recipient of public funding – in this case, directly with the University.

Do you have any questions about Open Data? Contact our Data Steward.
Ing. Tomáš Heryán, Ph.D.

Ing. Tomáš Heryán, Ph.D.

Data Steward CEET

tomas.heryan@vsb.cz
+420 596 997 429
Profile

Data Management Plan

It is always important to follow the principle “as open as possible, as closed as necessary.” A Data Steward not only advises researchers but also actively assists them in preparing and complying with a Data Management Plan (DMP) that describes Open Science procedures in detail. Sensitive data protected under GDPR, as well as sensitive dual-use data, cannot be made openly available; however, the DMP must clearly explain and justify such restrictions. Act No. 328/2025 Coll., on Research, Development, Innovation and Knowledge Transfer (§§ 7–8; §§ 37–40) also contains important provisions addressing unlawful influence by third parties on funding recipients.

In such cases, responsibility may also lie with the individual researcher, who may even, whether intentionally or unintentionally, incur criminal liability for negligence under Act No. 40/2009 Coll., the Criminal Code (§ 16(b)). This may concern, for example, situations in which the lead author of a research output demonstrably collaborates with co-authors affiliated with high-risk institutions, particularly institutions involved in the defence industry of countries outside the EU.

Clarivate’s Web of Science now provides tools for examining a researcher’s significant current and past collaborations. It is therefore essential to give greater consideration to the selection of co-authors and to research governance more broadly.