Data Management Plans - content

1. Learning Outcomes

Let's start with an outline of why the Data Management Plan is useful to historians. At the first workshop for the History DMT Project John Nicholls outlined his views of why it is so important.

It is very easy to simply focus on the research itself without considering how you will manage the resulting data as the project expands.  Data gathered during the research often has an enduring value beyond the initial purposes.  Research for a doctorate will seem at the time to be an enclosed piece of work, but after this is finished you will most likely find that you will need to revisit elements of this research for future projects some of which will be small, others might be large.  Without thought into data management it is likely you will have to retrace your steps, perhaps even recreate the original research from scratch.  Therefore a data management plan is important to safeguarding yourself from duplicating your efforts and does not take too long to complete.  The exercise is largely one of consideration about the managerial aspects of collecting and making data, but it is also one with which you can go away with a research plan in hand. 

Ask yourself this:

What is needed to validate the results of your research? 

If you were to produce an article researching, for example, the criminal underclass in early-twentieth century New York, what data would you need to include for someone else to replicate your results?  Think about it in terms of your own research.

A bibliography would be the most immediate and obvious starting point, revealing to the reader all the sources that you have used to base your research.  But what of the gathering mechanisms you used?  Did you create a database or undertake statistical analysis?  If so you need to make the database and statistics available.  This doesn’t just mean providing the files in a readable format, but to provide documentation and to make sure that the data is clearly identified with explicit headings, well-structured, and easily identified.

Focusing on what is needed for validation and re-use, rather than the obvious attributes of research data, is useful.  It helps you to think through the process of research from a different perspective and what it is you have actually done to come to your conclusions.  It also allows you to show the process you have undertaken; revealing how valuable your approach might be and making the data and research clearer for others to follow or replicate.

Therefore, it doesn’t necessarily matter if you plan to share your data with other scholars, what matters is considering this prospect as you work out how you are going to go about your research.  It will help you to understand what it is you are doing more clearly and give you the basis to share that data later on if you so wish.   

By the end of this book you will be able to:

  • Recognise a data management plan and its constituent parts
  • Explain the purpose of a data management plan and how you can apply it to your research
  • Started to construct your own data management plan