Data Stations

303,526
datasets

Social Sciences and Humanities

Archaeology

Life Sciences

Physical and Technical Sciences

Dutch national centre of expertise and repository for research data

Welcome to DANS, the Dutch national centre of expertise and repository for research data. We help researchers make their data available for reuse.
This allows researchers to use the data for new research and makes published research verifiable and reproducible.
DANS is one of the leading repositories in Europe.

Community experiences

"It is essential for scientists to share their data, because only then progress can be made and time can be saved. That is why it is good that DANS exists."

Prof.dr. Nicoline van der Sijs, Dutch Language Institute

"As a machine learning researcher, I understand all too well that there are no good models without good data. DANS plays a major role in this by not only making it very easy to share data, but also by incentivizing and giving proper credit to people sharing them."

Dr. Joaquin Vanschoren, Assistent Professor Machine Learning, Eindhoven University of Technology (TU/e)

"From my PhD advisor, I learned that information is the only resource that grows in use. That is why I greatly applaud sharing data via DANS."

Dr. Maarten Marx, Professor, University of Amsterdam

"Choosing a repository that can be trusted becomes an important issue to make our data widely spread, easily accessible, and available in the long term. DANS is a good repository that fulfills all of those criteria."

Diah H. Apriyanti, University of Twente The Netherlands & National Research and Innovation Agency Republic of Indonesia

"We often ask a lot of participants, both literally and figuratively. By sharing research data with each other, we can ensure that participants are less burdened."

Dr. Thabo van Woudenberg, Erasmus University Rotterdam

"Sharing data has proven to be a key success factor of our project. The very fact that we started publishing and sharing data online early in the project resulted in further participation of (unknown) private searchers and accelerated adoption by professional researchers."

Dr. Stijn Heeren, Project leader Portable Antiquities of the Netherlands (PAN)

"There is an abundance of places to put data — sharing with DANS gives me confidence that the data is archived properly and with integrity.”

Dr. Chris Hartgerink, Director Liberate Science GmbH

"The sustainable and centralised access to unique research data is invaluable to inform decision-making on preserving our cultural heritage. It is indispensable for individual researchers with a small but not insignificant research agenda."

Dr. Sanneke Stigter, Assistant Professor Conservation and Restoration of Cultural Heritage, University of Amsterdam

“Since 2012, our map of past and present Rhine-Meuse delta river branches are available via DANS, findable for archaeologists, hydrologists and others. We enjoy using the platform as an archiving and downloading place for our mapping data."

Dr. Kim M. Cohen, Faculty Geosciences, Utrecht University

"Our linguistic database of the Hebrew Bible is the product of more than four decades of hard work. DANS has helped us to reliably store this wealth of data and enable easy access."

Willem van Peursen, Professor of Old Testament, Faculty of Religion and Theology, VU & director of the ETCBC

News

Last month, I had the pleasure to give the opening keynote at the 18th edition of the International Digital Curation Conference (IDCC24) in Edinburgh. One of the many concerns of this age is the ability to trust information around us. Transparency is one way to promote trust, and in this sense the conference theme ‘Trust through Transparency’ struck me as both timely and relevant.

It is DANS’ mission to support you in making your data FAIR. We have therefore collected a number of frequently asked questions (FAQ) and published them on our website.

On 6 March 2024, MLCommons (an Artificial Intelligence engineering consortium) announced the release of Croissant, a metadata format to help standardise machine learning (ML) datasets. The aim of Croissant is to make datasets easily discoverable and usable across tools and platforms. This is highly relevant in the European Open Science Cloud (EOSC) tasks on FAIR data sustainability and important for Linked Data in general.