New to using data
Welcome to the resources section
Here you can find guidance and training to help you access and use data. From the learning hub you can browse resources about types of data, software, computational social science, research data management, geography, and teaching. Below, we highlight resources especially useful to new users. Watch our video guide: Tour of the UK Data Service website.
Secondary data analysis
Secondary analysis of qualitative and quantitative data
Secondary analysis is the reanalysis of either qualitative or quantitative data that has already been collected for a previous study, by a different researcher typically looking to address a new research question.
Research data are collected across a range of social science disciplines using a variety of research methods. Social surveys and interviewing projects represent the most common methods, but primary data can also be gathered from fieldwork observation, diaries, self-completion questionnaires and other activities. Administrative and routine business data collected in the course of government activities also represent a rich source of statistical information. These resources represent an abundant stock of material that can be reanalysed, reworked, used for new analyses, and compared or combined with contemporary data.
In time, archived data become historically important research materials. Using existing data also enables research where the required data may be expensive, difficult or impossible to collect, for example in the case of global administrative data, large-scale surveys or historic data.
The Economic and Social Research Council (ESRC) promotes secondary analysis through its Secondary Data Analysis Initiative (SDAI). The aim is to deliver high-impact policy and practitioner-relevant research through the deeper exploitation of major data resources.
Find out more about secondary analysis from our Reusing qualitative data guide (PDF).
Data skills modules
We provide on-demand interactive modules, designed for anyone who wants to start using secondary data.
Cite data correctly
Any research publication, whether printed, electronic or broadcast, based wholly or in part on the data collections accessed through the UK Data Service must be accompanied by the correct citation and acknowledgement information. And it is best practice to cite any data correctly.
- Watch our video Why cite data? Experts from the University of Essex discuss why and how the research community should cite data correctly.
- For a quick overview, see our Top ten tips to citing data (PDF).
- For more information about the importance of data citation and the role of DOIs, see the ESRC data citation web page and brochure Data Citation: what you need to know (PDF).
- Read our blog Spotlight on #CiteTheData: Make the data count which discusses citation and the benefits it brings to researchers and research.
- Publishing and citing research data presentation (PDF).
- ICPSR video: Why should I cite data?
- Cite The Data – Communications Campaign Toolkit (PDF) for organisations wanting to promote data citation with their stakeholders.
- Reasons to cite data correctly.
Use our data citation tool
Our citation tool is designed to make citing data easy and straightforward. You will find it on every catalogue record page.
The tool provides you with a full and accurate citation for that dataset in a format of your choice e.g. APA, DataCite, Harvard.
By clicking on the select citation format box you will get a drop down menu of formats. Simply choose the format you require and the citation will change accordingly.
You can then copy and paste that citation and use it in the acknowledgements section of your research document.