Working with research data

Data Management depends on the correct software to enable best practices. Oxford Brookes University uses Google to provide active data storage. The researcher should also consult the Portable Devices and Removable Media Acceptable Use Policy for guidance on other forms of data storage. Data management and collection software can involve large-scale computing, but it can also be as simple as a systematic literature review in Endnote. Information Security advises using only software that has been through the Oxford Brookes review processes. 

Oxford Brookes provides training for some supported software. For example, any research with a geographical or mapping component can use ArcGIS. For surveys and interviews, there is Qualtrics, Nvivo, and SPSS. Some research training for data analysis is available. Research data management encourages data reuse and preparation of data for reuse. Code books, ethics applications, fieldwork notes, contracts and general data documentation should be kept together with the data. The Data Documentation Initiative is helpful in this regard. Researchers collecting data should also communicate with their Research Leads about available support.

AI tools have become easier to use, so many researchers may be considering using AI-assisted methods. Researchers using data and AI techniques need to be aware that using any human subject data is complex. Anonymised data can be inadvertently re-identified - jigsaw identification - by linking datasets and using artificial intelligence techniques. It is advisable to review the Institute for Ethical AI information for help. 

Research software development to create bespoke software as part of the research methodology, is sometimes necessary when standard solutions will not work. Code creation often involves using and creating test data, either real or fictional. Software development requires a specialised data management plan called a Software Management Plan.

For best practices, sandboxes and advice, please refer to IT Services for Research

Researchers should try to anticipate what will be needed to make the data worthwhile for analysis. The definition of data quality varies between fields but will always involve some processes that can demonstrate academic rigour. Quantitative data should be managed according to the standard of the field, for example, Data Principles. Students can book tutorials and statistical resources are available for student projects that train students in these techniques.

Information governance ensures that Oxford Brookes University researchers can securely, ethically and legally collect personal and sensitive data. Researchers should classify data as it is collected. In a practical sense, working with sensitive data means following the procedures outlined and staying within the University's systems.

For more information, please refer to Information Security Management