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Data discovery & re-use

Data discovery & re-use

Many research projects require secondary data in order to address a proposed research problem, hypothesis or set of objectives.

In addition, the quantity of data, their qualities and how they are sampled and measured, has implications for the choice and effectiveness of the data analysis techniques used in subsequent analysis. Therefore, it is important that you use the correct data for your research.

This guide provides information on data discovery, citation, copyright and analysis.

Finding data for re-use

Data are increasingly available in open data archives. The Registry of Research Data Repositories (re3data) is a global registry of research data repositories across all academic disciplines. However, some data are only available through subscribed databases. You can view our list of databases, and also specialist guidance for finding sources of socio-economic data.

Your site or subject librarian will be able to advise you of relevant data sources in your subject area.

Finding publications

Use Explore, as part of your literature review, to search for research studies based on secondary analysis of publicly available datasets. Books on your topic may cite relevant data providers, or volumes with statistical tables may identify sources of data.

Library Services also provides access to a wide range of bibliographic databases for finding journal articles and a range of other material. Your site or subject librarian will be able to advise you of relevant databases.

Finding projects & UCL researchers' profiles

IRIS, the research portal for UCL, can help you to identify the research activities of researchers, research groups, research centres and interdisciplinary networks across the whole of the institution. You can search for researchers, publications, activities, groups, themes and departments.

Citing data

Data are legitimate, citeable products of research, just as other research outputs, so you must cite data.

  • A Digital Object Identifier (DOI) is often included in data citations. This ensures that even if the location of the data changes, the DOI will always link to the data that were used. DCC guidance has further information on citing physical data (see below).
  • Each dataset used must have a separate citation.
  • If your department, discipline or publisher recommends a specific reference style, follow the appropriate form for citing data. For example:

    • The Harvard citation style uses the following format:

      Author names. Year. Title of resource. [medium type]. Host institution name, Physical location. Date of access. Identifier

      e.g. Institute for Social and Economic Research. 2011. Understanding Society: Wave 1 2009-2010 [data file]. University of Essex, Colchester, Essex. Accessed 29 May 2015. SN: 6614. http://discover.ukdataservice.ac.uk/doi/?sn=6614#

    • The Vancouver citation style uses the following format:

      Author names. Title of resource [medium type]. Host institution name: Physical location; Year of publication. [Date accessed]. Available from: Identifier

      e.g. Institute for Social and Economic Research. Understanding Society: Wave 1, 2009-2010 [data file]. University of Essex: Colchester, Essex; 2011. [cited 29 May 2015]. Available from: DOI: http://discover.ukdataservice.ac.uk/doi/?sn=6614#

For more information, see the DCC guide 'How to cite datasets and link to publications', 'Why cite data?' from Datacite and the IASSIST 'Quick guide to data citation'.

Handling copyright & Intellectual Property Rights issues

Information is available to help you understand how to use copyright materials in your own work and in teaching. Useful background information is given, including explanations on Creative Commons licences

If you have issues with Intellectual Property Rights, copyrights and licences for your own data, check our recommendations.

The UCL copyright blog gathers answers to a large range of questions on re-using data.

Analysing data
  • UCL provides access to statistical software including: Excel, Matlab, R, SPSS and Stata.
  • ISD offer a range of training, how to guides and assistance with statistical software.
  • Lynda has a number of video tutorials on these packages, while SAGE Research Methods includes handbook, journal and reference content on secondary data analysis.
  • Explore will allow you to find manuals on data analysis available from our libraries.