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The following comment refers to this/these guideline(s)

Guideline 13

Providing public access to research results

As a rule, researchers make all results available as part of scientific/academic discourse. In specific cases, however, there may be reasons not to make results publicly available (in the narrower sense of publication, but also in a broader sense through other communication channels); this decision must not depend on third parties. Researchers decide autonomously – with due regard for the conventions of the relevant subject area – whether, how and where to disseminate their results. If it has been decided to make results available in the public domain, researchers describe them clearly and in full. Where possible and reasonable, this includes making the research data, materials and information on which the results are based, as well as the methods and software used, available and fully explaining the work processes. Software programmed by researchers themselves is made publicly available along with the source code. Researchers provide full and correct information about their own preliminary work and that of others.


In the interest of transparency and to enable research to be referred to and reused by others, whenever possible researchers make the research data and principal materials on which a publication is based available in recognised archives and repositories in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable). Restrictions may apply to public availability in the case of patent applications. If self-developed research software is to be made available to third parties, an appropriate licence is provided.

In line with the principle of “quality over quantity”, researchers avoid splitting research into inappropriately small publications. They limit the repetition of content from publications of which they were (co-)authors to that which is necessary to enable the reader to understand the context. They cite results previously made publicly available unless, in exceptional cases, this is deemed unnecessary by the general conventions of the discipline.

Making Research Results Accessible in the Life Sciences

The aim should always be to publish a full set of results, since correct correlations and new insights can be gained more effectively and efficiently based on a comprehensive overview of previously elaborated research outcomes. When evaluating results, the focus should be on careful description and validity.

In order to ensure units of meaningful content, quality must be the main focus when planning publications. When a researcher presents their own publication record, care should be taken to list only a selection of papers.

Consideration of the FAIR principles in handling research data is particularly crucial in the collaboratively oriented life sciences so as to ensure verifiability and reuse of results. The answer to many questions in the life sciences is based on the evaluation of complex data sets or the modelling of processes based on data sets. This is often the only way to understand complex, broader insights. The implementation of the FAIR principles draws heavily on resources and time. Due to the great diversity of data types, which is further increased by the dynamics of methodology and technique, researchers often rely on the support and expertise of research data centres. This also ensures compatibility and interoperability of the data sets at both national and international level. It is advisable to start thinking about this during the project planning phase so as to allow for the necessary human and financial resources.       

In the case of clinical research questions in particular, data protection aspects can be relevant when it comes to enabling access to data sets and their collaborative use. In these cases established pseudonymisation methods should be applied, as well as technologies for evaluating the re-anonymisation risk. It will frequently be possible to work with anonymised data sets to answer the research question.

In the life sciences, it is very often the case that research data is very closely linked to materials, tissues or organisms. Access to these is often equally important when it comes to ensuring that findings are verifiable and compatible. For this reason, approved and certified archives, collections or biobanks should be used so as to ensure that the central pool of materials, tissues or organisms relating to a project is kept available in a standardised form and in the best possible quality. The time and financial resources required for this are aspects that need to be considered early on, during the project planning phase. This is particularly relevant in the case of microbiological strains and human material.

If research results are available in the form of a software, model or simulation, or if machine learning methods have been used, provision of all the information necessary for verifiability and compatibility poses a challenge. In the case of software, it is advisable to facilitate reuse by means of containerisation and integration in frameworks such as Bioconductor, for example. The source code should be disclosed wherever this is possible and reasonable. Publication of training datasets allows better verifiability and reuse of the results of machine learning processes

The comment belongs to the following categories:

GL13 (Life sciences)