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Creating & analysing data

Creating & analysing data

This section contains information on collecting, analysing, organising and describing data (including metadata creation).

You will also find guidance on sensitive and personal data, on formats of data, and on software that you may need for your research project.

Collecting data

In the absence of existing data to re-use, you will frequently have to create unique data to test the hypothesis outlined in your project proposal. Whether you generate primary sources via fieldwork or sitting at your desk, your tutor or Principal Investigator will be the main source of information on how best to collect your data in the first instance. 

PhD students will benefit from enrolling in courses run by the Doctoral Skills Development Programme

An Intellectual Property Rights (IPR) Agreement should be in place for all research projects. Guidance to UCL staff and guidance to UCL students on IPR issues is available.

Collecting sensitive & personal data

Sensitive and personal data are useful sources of information for many disciplines. They deal with living, identifiable individuals and/or delicate issues related to human participants or third parties. You must anticipate as early as possible the ethical and legal questions that will arise as part of your research. You are responsible for ensuring your handling of all this information is secure and complies with the law.

You will find information to check if your research data are personal and/or sensitive. Our guide dedicated to handling such data will help you identify these legal and ethical questions. 

Explore will enable you to find manuals available from our libraries on qualitative research methods to collect such data. You can also use SAGE Research Methods to find online resources.

It is a good idea to check for discipline-specific and professional ethics codes. The ESRC provides a list of such codes on its Research Ethics resources.

Organising data

UCL Records Office provides guidance on how to organise your data and all of the files used during your research project. You will find information on

Essential information on how to protect research data is also available.

Choosing your formats

The format of your data should be chosen very early on in your project. That choice will depend on the type of data that you will gather. For example, text, image and audio-visual data all require different considerations. You will also need to take into account any discipline-specific recommendations and any funder's expectations, as well as consider how you plan to analyse, store and share your data.

In our guide on formats you will find help to make decisions around formats, along with advice on recommended formats, long and short term formats, dissemination and preservation formats, and proprietary formats.

Describing your data: metadata and documentation

When preparing to collect your research data, it is important to choose a method to describe them. This choice should be made as early as possible to enable a consistent description across your project and to save time once you will start to share your data and outputs with your audience. You will need to take into consideration discipline-specific recommendations, funder's expectations and your storage and dissemination plans.

Metadata

If you don't need to follow a discipline-specific schema, or funder's recommendations, then we advise you to use the DataCite metadata schema (see p.7 for a summary table). 

As a general rule DataCite recommends that your metadata should at least specify

  • an identifier (a DOI), 
  • a creator (the name and affiliation of the main researchers involved in producing the dataset),
  • a title (the name or title by which the dataset is known),
  • a publisher (the name of the entity that holds the dataset),
  • a publication date (the year when the dataset was or will be made publicly available) and
  • the type of resource you are describing. 

If you think that your data requires description with fields that are not covered in the DataCite schema, please contact the Digital Curation Team for advice.

Documentation

Documentation, like metadata, should accompany data to ensure that these are easily discoverable, understandable and re-useable by other researchers without the help of the data creators. You can choose to document your data in two ways:

If you have any questions regarding metadata and documentation of data, please contact your Research Data Support Officers or the Digital Curation team.

Analysing data

Many resources are available to UCL students and staff to help with research data analysis.

  • Explore will enable you to find manuals available from our libraries on methods to analyse your data.
  • To help you analyse qualitative and quantitative data, you can use software such as NVivo, Excel, Matlab, R, SPSS and Stata. ISD offers a range of training opportunities and assistance with these software.
  • Lynda has a number of video tutorials on these packages, and SAGE Research Methods includes handbook, journal and reference content on secondary data analysis.

Improving and developing software for researchers

UCL Research Software Development team can help you with the software that you are developing for your research project, or which has been developed by your research group. Research Software development infrastructure, training and support are available.