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| Raw simulated data for contextual seriation (Wikipedia) |
On winding up a research project recently, I got to thinking about
the ideas and data points that didn’t make it into the final
publications or conference presentations.
After collecting survey responses and focus group transcripts, the research team looked over the findings and decided how to divide it up into publishable chunks.
Then for each paper we took the data that was relevant to that topic, analysed it thoroughly, and then decided what the main argument could be - that is, what is the new knowledge gained from that part of the research?
But there are still a few intriguing bits and pieces of data left over. The process brought home to me how often doctoral writers are faced with ideas and data that don’t quite fit into the scope of the doctorate. To avoid feeling that work is ‘wasted,’ it is helpful to think about how those leftovers might be used.
In doctoral research projects, as with any quality research, ensuring that the work has followed rigorous research methods and thus produced reliable data helps us answer the research question we set out to address in the first place.
When it comes to doctoral writing, the integrity of the methods and the interpretation of the resulting data are presented in the thesis, keeping a close eye on examiner expectations. Obviously, this is central to how a doctoral study proves itself worthy of a PhD.
Elsewhere in the DoctoralWriting blog I have written about the importance of constructing a thesis that is not simply an exact record of all the components of the research journey - decisions need to be made about what needs to be left out of the thesis, just as much as what needs to be included.
Having constructed the thesis version of the research for doctoral examination, there are likely to be bits and pieces of data that don’t find their way into the main argument, that seem to be left over at the end of the project. Sometimes, though, these leftover items of data stay in the researcher’s mind, hinting that there is more to be said about the topic, niggling away in the background and refusing to be put aside.
I firmly believe that there is a place for the intuitive hunch in research, the idea that attracts attention even when it is not fully worked out, the idea that seems to be left over from the main project. I have taken heart from the work of Maggie McLure in relation to this.
She writes about data that ‘glows’, by which she means ‘some detail - a field-note fragment or video-image - [that] starts to glimmer, gathering our attention’ (McLure 2010: 282). McLure provides us with an example of how she works with such data in ‘The Wonder of Data’ (2013).
These glowing data points tell us something interesting, but maybe it’s not always a really big idea or argument that is to be made, at least in relation to the current research project. Or perhaps the glowing data stands out from what’s already been said, not contradicting the main argument (of course!), but moving off on another tangent.
It might be something really interesting even though it does not fit logically alongside the central point of the thesis chapters or articles that finally make it to the light of day.
I’ve starting thinking that perhaps an important role for research blogs is to provide a place to explore leftover data that may or may not turn out to be big ideas. When writing for the DoctoralWriting blog, I often find myself exploring ideas that start out tiny, and maybe grow into a blog, and occasionally continue to blossom into a full-sized research project.
For doctoral candidates, publishing one’s work through blogs is not always straight forward and should be approached cautiously. But perhaps a similar process of writing up short pieces that may later be revisited can be a useful practice. This procedure has the advantage of not throwing away the data that doesn’t make it into the final thesis, and of encouraging ongoing writing habits.
I’m not sure that the leftover data is a concern for all doctoral researchers, though. Perhaps the possibility of confronting leftover data is more common in qualitative research, for example, where interview participants might expand on related ideas that are not quite directly on the main topic of the formal interview questions.
In workshops I remind students that nothing is ever wasted in the work they do towards their research, and suggest that it’s good to keep any extra ideas in a separate file if they don’t seem to fit into the main thesis. I too have got one of those files and it seems to keep growing, but at the moment I’m not quite sure what I can do with it.
I’d be interested to hear from readers who have made good use of leftover data from their research, especially those who undertake quantitative studies (can ‘outliers’ be informative in unexpected but useful ways?). I suspect that the leftover data that glows can inspire us towards new research directions, whatever our methods.
After collecting survey responses and focus group transcripts, the research team looked over the findings and decided how to divide it up into publishable chunks.
Then for each paper we took the data that was relevant to that topic, analysed it thoroughly, and then decided what the main argument could be - that is, what is the new knowledge gained from that part of the research?
But there are still a few intriguing bits and pieces of data left over. The process brought home to me how often doctoral writers are faced with ideas and data that don’t quite fit into the scope of the doctorate. To avoid feeling that work is ‘wasted,’ it is helpful to think about how those leftovers might be used.
In doctoral research projects, as with any quality research, ensuring that the work has followed rigorous research methods and thus produced reliable data helps us answer the research question we set out to address in the first place.
When it comes to doctoral writing, the integrity of the methods and the interpretation of the resulting data are presented in the thesis, keeping a close eye on examiner expectations. Obviously, this is central to how a doctoral study proves itself worthy of a PhD.
Elsewhere in the DoctoralWriting blog I have written about the importance of constructing a thesis that is not simply an exact record of all the components of the research journey - decisions need to be made about what needs to be left out of the thesis, just as much as what needs to be included.
Having constructed the thesis version of the research for doctoral examination, there are likely to be bits and pieces of data that don’t find their way into the main argument, that seem to be left over at the end of the project. Sometimes, though, these leftover items of data stay in the researcher’s mind, hinting that there is more to be said about the topic, niggling away in the background and refusing to be put aside.
I firmly believe that there is a place for the intuitive hunch in research, the idea that attracts attention even when it is not fully worked out, the idea that seems to be left over from the main project. I have taken heart from the work of Maggie McLure in relation to this.
She writes about data that ‘glows’, by which she means ‘some detail - a field-note fragment or video-image - [that] starts to glimmer, gathering our attention’ (McLure 2010: 282). McLure provides us with an example of how she works with such data in ‘The Wonder of Data’ (2013).
These glowing data points tell us something interesting, but maybe it’s not always a really big idea or argument that is to be made, at least in relation to the current research project. Or perhaps the glowing data stands out from what’s already been said, not contradicting the main argument (of course!), but moving off on another tangent.
It might be something really interesting even though it does not fit logically alongside the central point of the thesis chapters or articles that finally make it to the light of day.
I’ve starting thinking that perhaps an important role for research blogs is to provide a place to explore leftover data that may or may not turn out to be big ideas. When writing for the DoctoralWriting blog, I often find myself exploring ideas that start out tiny, and maybe grow into a blog, and occasionally continue to blossom into a full-sized research project.
For doctoral candidates, publishing one’s work through blogs is not always straight forward and should be approached cautiously. But perhaps a similar process of writing up short pieces that may later be revisited can be a useful practice. This procedure has the advantage of not throwing away the data that doesn’t make it into the final thesis, and of encouraging ongoing writing habits.
I’m not sure that the leftover data is a concern for all doctoral researchers, though. Perhaps the possibility of confronting leftover data is more common in qualitative research, for example, where interview participants might expand on related ideas that are not quite directly on the main topic of the formal interview questions.
In workshops I remind students that nothing is ever wasted in the work they do towards their research, and suggest that it’s good to keep any extra ideas in a separate file if they don’t seem to fit into the main thesis. I too have got one of those files and it seems to keep growing, but at the moment I’m not quite sure what I can do with it.
I’d be interested to hear from readers who have made good use of leftover data from their research, especially those who undertake quantitative studies (can ‘outliers’ be informative in unexpected but useful ways?). I suspect that the leftover data that glows can inspire us towards new research directions, whatever our methods.
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