In parallel to the publication of your research findings in a reviewed journal, it is recognized as good practice (and often required) to make the data that support your findings available to the research community. This allows other researchers to reproduce your findings and enables reusability in subsequent research. When you finish your study, you might thus want or have to make your data accessible. This page provides useful information to help you publish and disseminate your data.
For the publication of research data, repositories are available that make it possible to publish the data together with the documentation and metadata and make them findable. Publication of data on a website is not recommended for reasons of poor sustainability and discoverability of the data.
Not all data can and may be shared publicly. Ethical and legal aspects must be considered here and must definitely be clarified in advance. It does not always make sense to publish all the data from a research project. If only part of the data is suitable for subsequent use, a selection of the data or only certain data sets can be published.
Most research funders require that data be published in compliance with the FAIR principles. This implies that, in addition to documentation and metadata, the data must also be given a persistent identifier so that it can be cited. To make the data interoperable and reusable, the data should be provided in common or open file formats and accompanied by licences for use (CC licences).
For data that cannot be published for legal reasons, at least the metadata should be made publicly available.
Research data repositories are specialised online platforms where research data can be uploaded and shared together with the related metadata. They have a search function that can be used to find the datasets. Most repositories allow to assign persistent identifiers to ensure citation and referencing. For data that cannot be shared publicly (e.g. personal data) there are repositories that allow data to be stored with restricted access or made available after an embargo period. In this case it is important to provide information on the conditions of access.
We differentiate between three different types of repositories:
Another distinction is made between commercial and non-commercial repository providers. Here it is important to consider the requirements of the research funding organisations, as data uploads to commercial repositories are not always funded. An example of a commercial repository is Figshare.
For certain domains there are national repositories in Switzerland, e.g:
The Swiss National Science Foundation (SNSF) provides a list of generalist, discipline-specific and institutional data repositories.
Another way to search for repositories is the Register of Research Data Repositories re3data.
See also:
Research data are becoming increasingly openly available through data repositories, data journals and supplementary material in scientific journals.
To find research data there are different options:
Bioschemas aims to improve data interoperability in life sciences. It does this by encouraging people in life science to use schema.org markup, so that their websites and services contain consistently structured information. This structured information then makes it easier to discover, collate and analyse distributed data.
When you re-use a dataset, it is important, for reasons of transparency and good scientific practice, that you cite the data and give credit to the original data creator(s). The citation should include the following information about the dataset:
The way you arrange these elements depends on the citation style you use.
In many cases, when you find a dataset in a repository, you will be given a suggestion of how to cite the dataset and can sometimes also choose between different citation styles.
Example for the citation of a dataset:
Krasselt, J., & Dreesen, P. (2024). Topic model and n-grams for islamophobic blog PI-News (Version 1.0.0) [Data set]. LaRS - Language Repository of Switzerland. https://doi.org/10.48656/k36q-aq92.
Persistent identifiers allow resource providers (e.g. journals, repositories, …) to uniquely reference persons, datasets or other types of publications. The most prevalent of these identifiers in the research community are the DOI and the ORCID.
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