Promote your research data

Promoting your research data

How can you ensure that others (re)use your data? How do you make your data as impactful as possible?

Consider stimulating (re)use of your data in one of the following ways:

Deposit your data in a data repository

It is important that your data can be found by others. Make sure your (meta)data is available online by depositing it in a data repository. Researchers at Tilburg University can make use of the certified data repository DataverseNL.

Choose open data

When depositing your research data in a data repository, choose (where possible) for open access. If researchers have free access to your data, it is more likely that your data will be reused and have an impact on their work. See also the Tilburg University websibe on Open Science.

In a data repository like Tilburg University Dataverse it is possible to control access to your data down to the file level. If your files are not fully open, a user can submit an "access request": a request for access to your file(s).  After this you can, possibly after contacting the requester, decide to grant or deny access. If you do not want the dataset to be used by third parties at all, the option "restricted without access request" is available in Dataverse. For more information about the different options when archiving and sharing your data in TiU Dataverse see Tips on depositing datasets in Tilburg University Dataverse.

License your data

Assigning a license to your research data is important for the future impact of your data. Researchers may not use your data if it is unclear to them what is allowed with your data. For more information on licenses, see the page publishing and sharing research data.

Quote your data

Make sure you always quote your data and link it to the scientific publications based on this data. Always use the persistent identifier—usually DOI—assigned to your data by the data repository. A citation of a DataverseNL dataset looks like this:

  • Kamoen, Naomi; Holleman, Bregje; Struiksma, Marijn, 2020, "The emotional resonance of negativity: two experiments on valence framing in L1 and L2",, DataverseNL, V1

More information and examples  

Publish in a data journal

Consider publishing an article about your data in a data journal. These journals have been created to document and publish data sets extensively. They facilitate and stimulate online exploration and reuse of your data. Examples of data journals for the social sciences and humanities are:

  • Research Data Journal for the Humanities and Social Sciences (RDJ, Brill, 2017);
  • Journal of Open Psychology Data (JOPD, Ubiquity Press);
  • Journal of Open Archaeology Data (JOAD, Ubiquity Press);
  • Open Health Data (Ubiquity Press).

Use your data in your education

Consider using your data sets during one of your lectures (or those of others) with instructions on how to use the data set.

Increase the impact of your data with altmetrics

Altmetrics or alternative metrics are alternative parameters that show the impact of your data. Data is increasingly being shared in data repositories and quoted in publications. Most repositories assign a DOI to data sets. Such an identifier makes it possible to measure how often the data set is:

  • quoted;
  • viewed or downloaded;
  • stored in online literature management systems;
  • mentioned in online news media or on social media.

After depositing your data set in a data repository and assigning a DOI, consider:

  • writing a blog post or article about your dataset;
  • tweeting about it;
  • writing about it on Facebook or Instagram;
  • etc.

Do not forget to add a citation, DOI or web link (URL) that redirects to your dataset in the data repository.  This is the only way to keep track of how your data is used, viewed, and labeled.

Follow your data sets

Published data sets can be tracked in two ways (Ball & Duke, 2015).

Citation based metrics measure the number of citations of your data set by other researchers. Examples of these metrics are:
Altmetrics based metrics measure how often a data set (or other research related publication) has been shared, named, and downloaded from online sources such as social media, blogs, news media, and reference managers (such as Endnote and Mendeley). Examples of these alternative metrics are:

Alternative metrics have a number of advantages over traditional metrics based on the number of citations.

  • Immediacy
Whereas traditional metrics often have a considerable delay between publication and citation, alternative metrics give an up-to-date idea about the use of and attention for your data set/publication.
  • Connection
Measure the range and influence of your work. How is your research discussed and shared online? Who is talking about your work? Academics? The general public? Where do they come from?
  • Additional
Alternative metrics together with traditional metrics can give a more complete picture of the impact of your work.