Data archives

For researchers, the move to open data means that they have to think about what data their research will produce, how these data will be described, and how they can be made available in such a way as to benefit science and society in general. This means that they have to draw up a data management plan and find suitable data depositories. | ERC, 2019

Where is the best place for researchers to publish their research data? This section discusses the considerations and discusses a number of possible data archives.

Recommending a data archive

After the choice for data publication, the choice for a data archive follows. Whereas research projects often have a short lead time, data archives focus on continuity and long-term availability and reusability. Data archives play an undeniable role in facilitating a FAIR data infrastructure.

Which data archive can you recommend to researchers? Sometimes this is already prescribed by a funder, publisher or other external party. But if a researcher has to make the choice for him- or herself, you can, for example, follow the recommendations by OpenAIRE (n.d.) or from ERC (2019).

1. Choose a discipline-specific and trusted data archive with a quality seal

First, recommend a domain-specific data archive. The advantage of a discipline-specific data archive is that the possibilities are much more focused on the research community in question. The data can be described in a richer way through the use of discipline-specific metadata standards, which also increases the possibility of finding relevant data.

For examples of discipline-specific archives take a look at the recommended repositories by PLOS ONE (n.d.) or the list by ERC (2019).  

When making your final choice, ask yourself the following question:

  • Is the data archive committed to long-term access?
  • Does the data archive store the data safely?
  • Does the data archive ensure that the data remain findable through the use of persistent identifiers? 
  • Does the data archive describe the data in a standard manner, with accepted metadata standards?

If the data archive has a data quality mark such as the CoreTrustSeal, this can be assumed. 

In the Netherlands, you can make use of (DANS, n.d.a.) or 4TU.Centre for Research Data (n.d.). For large datasets there is also the SURF data repository (SURF. n.d.). Have a look at the infographic for this.  

2. See if an institute repository is available

If a domain-specific data repository is not available, see if an institution repository exists.

3. Choose a generic data repositoy

If none of the above is available, recommend a general purpose data repository:

4. Find a repository at

To discover other data repositories, search (n.d.), a register of more than 1500 data archives and repositories. You can search by subject, content type and country. In addition, you can search for data archives with a quality seal, with datasets that are available via open access or that have a persistent identifier.

There are hundreds of repositories worldwide. Some cater to a specific research domain, while others are general-purpose repositories. They may be called something other than a repository, for example, a data centre or an archive. | Whyte, 2015

In the spotlight

Decision tool for choosing a data archive in the humanities (DARIAH-EU)

DARIAH has developed a data deposit recommendation service for the humanities. You can give it a try over here (DARIAH-EU, 2017).


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4TU.Centre for Research Data (n.d.) Archive your research data.

DANS (n.d.a). DANS EASY.

DANS (n.d.b.). DataVerseNL.

DARIAH-EU (2017). Data Deposit Recommendation Service for Humanities Researchers

Dryad (n.d.)

ERC (2019). Open Research Data and Data Management Plans. Information for ERC grantees by the ERC Scientific Council.

Figshare (n.d.)

Harvard University (n.d.) 

OpenAIRE (n.d.). How to find a trutstworthy repository for your data.

Open Science Framework (n.d.)

PLOS ONE (n.d.). Data Availability.

Re3Data (n.d.)

SURF (n.d.). SURF Data Repository.

Whyte, A. (2015). ‘Where to keep research data: DCC checklist for evaluating data repositories’ v.1.1 Edinburgh: Digital Curation Centre. Available online:

Zenodo (n.d.)