Find and Use Data

Researchers often store and publish their data in so-called repositories, i.e. digital archives. There are thousands of repositories that make data openly accessible so that it can be used for one's own research.

There are generic, institutional and discipline-specific repositories. The best way to find existing data for reuse is by searching in discipline-specific repositories. How to start your search:
 

• Ask the community: Which repositories are generally used by other researchers in your discipline?
• Recommended repositories of research funders : Both the SNSF  and the European Commission maintain lists of subject-specific data repositories.
• re3data.org is another good starting point for your research. re3data.org is currently the most important and largest registry of research repositories world-wide.

Once you have found a relevant repository, you can limit the search for a suitable dataset further.

• Identify relevant keywords and search terms (be careful to narrow down this list as much as possible, e.g. only look for keywords in abstract and title but not also in author name) or categories.
  See also UB UZH's Good search tips
• Evaluate datasets for their technical and legal reusability. Choose data in open formats and with a license that allows for re-use .
  More information ondata formats andlicenses.
• Evaluate the quality of data documentation. The more you know about a dataset from the documentation, the better you can assess the suitability of the data for your own project.

• Subject = filter by discipline
• Data Licenses = data are licensed for reuse
• Data Access = data are openly accessible
• PID (persistent identifier) = the repository assigns persistent identifiers to its objects, e.g. DOIs.

In order to be able to work with your found data, you must have the appropriate rights. You must also comply with the terms and conditions of the license. Only then can you process the data further. For further processing (and proper data management) you would also document your reuse and then cite the data in the publication.

more information on copyright

understanding licenses

data documentation

Sometimes the repository indicates how the data should be cited. If the dataset comes with a DOI, you can use crosscite  to create a citation.

Generally we recommend to include the following information in a citation:
Creator (PublicationYear): Title. Publisher. (resource type). Identifier. 

Example:
Pidgeon, Nicholas and Demski, Christina and Stuart, Capstick and Alexa, Spence and Sposato, Robert (2016). Public perceptions of climate change and personal experience of flooding. [Data Collection]. Colchester, Essex: UK Data Archive. 10.5255/UKDA-SN-851835

Science IT supports UZH researchers in technical matters for software solutions, data storage, data management and data visualization.