Big data, small data, no data

This week, a guest post from Patricia Herterich, Research Repository Advisor in Library Services, on managing your research data.

There are many aspects to a successful PhD project and challenges to master on your way to graduation. You most certainly are aware that you should acquire e.g. writing and referencing skills, but how much time have you spent thinking about the research data management activities you might need to undertake as part of your research?  None yet? Time to get started with our introduction to research data management!

First of all: identify your data!

The term research data describes all the evidence underpinning your research. Depending on your research area, data can range from statistics, measurements, survey data, interview recordings and transcripts to collections of images, published texts, artworks or other objects.  (Yes, this also applies to arts and humanities!)

Why should you manage your data?

There are several selfish reasons to organise and document your research data from the beginning of your PhD project. Proper management and back-up practices reduce the risk of the ultimate nightmare – losing your data. Well documented data makes it easier for your supervisor to understand your research, spot mistakes and thus help you get the best result. It also makes your own life easier as you can just pick up where you left after a break (or use your data for a follow up project after graduation). If you have managed your data well, writing papers – and your thesis – will be faster since you can profit from the work you have already done on documenting your data and the analysis.

You should also consider publishing your data – unless it is personal data or commercially sensitive – so others can build on your work and validate your results. Good research is reproducible!

Revising his paper, the grad student is unable to replicate his own statistical results (reproduced with permission)

Don’t be like the Lego Grad Student – manage your data and document your analysis!

So… where to start?

A good first step is trying to write a so called data management plan (DMP for short). The UoB template for such a document is available here. Though you might not be able to provide answers to all the questions immediately, trying to write a DMP gives you some food for thought and can prevent forgetting about certain issues until it’s too late.  A DMP should be a living document that you get back to and update it whenever you change your data creation process, storage options or anything else.

This is complicated and confusing…

Don’t worry. We have created a self-enrol CANVAS course and information pages where you can read up about research data management (RDM) at your own convenience. If you would like to get face-to-face training, talk to your supervisor to have a bespoke training session set up for you and your research group, or contact the Postgraduate Development Officer.

Do you have more questions about RDM and would like to read more about it on this blog? Let us know in the comments below!

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