This is nothing new, but datasets are still somehow overlooked. Data sets, whether they are measurements from experiments, photographs from a microscope, geographic map layers, genomic data, animal behavior records, clinical data, etc., can now be reported by scientists and research institutions as a separate result of type T - digital data collection to RIV. This step represents a fundamental shift in the recognition of scientific data as a full-fledged result of scientific work and supports the principles of open science and FAIR data.
What is this digital data collection?
The term “digital data collection” refers to any dataset in digital form resulting from research, created through a non-trivial process or a combination of such processes within the scope of the research project, which provides new utility for subsequent research, development, or innovation. As a result of the research project, a digital data collection must meet the following criteria:
– be accompanied by machine-processable and publicly available metadata in accordance with FAIR principles.
– be assigned a unique, machine-processable persistent digital identifier (e.g., via the “handle” system, which includes DOI and other types of persistent identifiers, or a similar long-term PID service),
– be assigned a binding license or terms for further use and distribution, including a description of new utility values for subsequent research, development, or innovation,
– be stored, including metadata, in a publicly accessible, trusted, or field-certified digital repository, such as repositories of major research infrastructures or the EOSC CZ National Repository Platform,
– have at least one author who participated in the conducted research.
Can or must?
The verb “can” is somewhat of a euphemism. In fact, according to Section 31(3) of Act No. 130/2002 Coll., there is an obligation to report digital data collections. Act No. 328/2025 Coll. on Research, Development, Innovation, and Knowledge Transfer, which replaces it as of January 1, 2027, takes exactly the same view. The difference is that this obligation is explicitly enshrined in Section 88.
The laws do not explicitly define what constitutes a research result. However, this is specified in Annex No. 1 of the 2025+ Research Organization Evaluation Methodology. Together with certain Academy of Sciences-specific provisions, this forms a binding framework for the evaluation of the Biological Centre as well.
So how am I supposed to do that?
It’s not as bad as it seems. We’ve already outlined the benefits of sharing research data. As long as you follow the FAIR principles, the rest is relatively easy.
1. In most cases, a digital data collection is linked to a specific publication (primarily a research article, conference paper, etc.). Once you publish an article, you must also make it available in the ASEP institutional repository. Depending on the project’s mandatory procedures, this may be as a bibliographic record or even as a full-text version. Simply hand over the materials to a colleague at the institute secretariat, as you are accustomed to doing under the Intellectual Property Management Directive. That colleague will then upload it to ASEP. The following year, everything is exported to RIV.
2a. If you have already published the data collection for the article in a trusted repository, e.g. on Zenodo, Figshare, etc. (after all, TOP publishers already require this), just provide this link (DOI) to the institutional Data Steward. He will create a data record with the existing link. Also provide the link to the data (DOI) to the colleague at the institute secretariat. He/She will link the article record with the data.
2b. Well, if you haven't published the data yet, you simply give the data collection to the data steward (in electronic form, of course), along with the names of the authors and affiliations, keywords, abstract, license (usually CC-BY or CCO), projects to which the set is linked, and possibly also the DOI of the article and ideally a so-called READme file with metadata (information about the data - how it was obtained, by whom, where, how it was processed, edited, etc.). Or you can agree with Data Steward on where and how you will publish the data. You can, of course, use a specialized repository.
3. And if you’re unsure, ask the project data steward (you surely count on having a data steward in the project!) or consult the institutional data steward.
