Does CAQDAS distance us or bring us closer to our data?

By Christina Silver on Oct 01, 2016 at 09:29 AM in CAQDAS commentary

by Christina Silver, 1st October 2016

Does CAQDAS distance us or bring us closer to our data?-3

In an earlier post on CAQDAS critics and advocates I promised to provide evidence for my position that CAQDAS packages are not distancing, de-contextualising, and homogenising, as is sometimes claimed. So I’m starting a series of posts. First I'm taking the suggestion that the use of CAQDAS distances us from our qualitative data and illustrate why I believe the converse to be true. Here I outline my position, and I'll illustrate my argument with examples in subsequent posts.


Does CAQDAS distance us or bring us closer to our data?

Being close to data is essential when undertaking qualitative analysis, whatever its form, the sources it comes from, or the strategies we use to analyse it. I have discussed this in relation to transcription as an analytic act, elsewhere, arguing that just like when children learn to read they must repeatedly revisit letter-sounds, words, sentences and stories to consolidate their learning, we as qualitative analysts must read and view our data multiple times in order to become sufficiently familiar with it to develop a nuanced, accurate and authoritative interpretation. Being “close to data” is therefore of utmost importance.



Does CAQDAS distance us or bring us closer to our data?-1
I'm not best-placed to outline the position that the use of CAQDAS packages distances us from our data, seeing as I don't believe they do. However, this suggestion has something to do with the idea that we need tactile and direct contact with data in order to reach the level of familiarity required for analysis. It is argued that this is achieved by working with hard-copy print-outs, marking interesting passages using highlighter pens and writing notes in the margin. We can flick back-and-forth through the pages, and visually annotate the associations we see. 
This is indeed what I did for my first two QDAs, my A-Level sociology project and undergraduate dissertation. In those days there were sadly only four highlighter pen colors, but I had other tactics at my disposal: scissors, post-it notes, blue-tac, and thread.
I photocopied transcript printouts, highlighted interesting segments, cut them out and constructed a matrix of themes by respondents on my bedroom wall. Most of the time I remembered to scribble on the back of each cut-out segment approximately where in the transcript it had come from and who had said it and I used thread to make links between related cut-outs. This is what I ended up with... 
Does CAQDAS distance us or bring us closer to our data?
It was fun and it sparked my interest in qualitative analysis. And I was certainly close to my data. It surrounded me in fact, I couldn't get away from it in my tiny student bedroom. But I faced a few challenges in managing the data, accessing the source context reliably and handling the fact that many of my cut-out segments related to more than one theme, and therefore belonged in more than one matrix cell.
The argument is that the use of CAQDAS puts some kind of barrier between us as analysts and our data, such that we cannot interact with it in the same way as when working manually, we cannot be close enough to it to reach the necessary level of familiarity.

What about non-textual data?

Does CAQDAS distance us or bring us closer to our data?-6
Many researchers work entirely or predominately with textual forms of data, but what about when audio, video or graphic data are our sources? We have to use technology to capture and view these data. We could print graphics out and analyse them by hand, but that's not possible with audio and video. I'm not sure where the close-to-data-critics stand on this point...


I believe that CAQDAS tools, when harnessed appropriately, can bring us way, way closer to data than is possible when working with hard-copy or using non-dedicated software (such as word processing and spreadsheet applications). 


Does CAQDAS distance us or bring us closer to our data?-2

For me, it all has to do with the reliability and speed of access. As soon as we use a dedicated CAQDAS package we are able to create links within and between all of our materials and all of the ideas we have about them. Once we start doing that - and there are several ways we can do it - we can access anything and everything related to any bit of material and any part of our analysis, whenever we want, however we want, for whatever purpose we want. Reliably, quickly and repeatedly. And that means we can review it, revise it, build on what we have done before. And so it continues. And we can do it with any form of data our CAQDAS package supports. 

Flicking back-and-forth takes on a whole new meaning. 


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And its not just our “data", but all the materials that are relevant to our study. Grant proposals, previous literature, supplementary information, internet content, notes we have made about our participants, about our data, about our processes, about the ideas we have had about about anything during the process that we have recorded within our CAQDAS project or linked to from it. We can access earlier work we have done, review it, alter it, write about it. Build on it. 


The suggestion that CAQDAS packages distance us from our data is mystifying to me in part because it ignores the status of our interpretations, somehow prioritizing "data" above and beyond our description, analysis and interpretation of it. Sure, the datasets we construct in order to answer our research questions are important, fundamental even, but what we produce as the result of the work we do is always some form of account of that data, not the data in its raw format. We do of course illustrate our accounts with extacts of data, but the account itself is some sort of structured synthesis, summary, representation, pathway through, or reduction of it. Depending on our objectives and guiding methodology the account might be presented as a theory or model, it might be presented as a narrative, it might be presented as visually or dynamically. 
Does CAQDAS distance us or bring us closer to our data?-7
Using dedicated CAQDAS packages enables us to keep all the insights we have about our data, throughout the process, stored together with our data. Moreover, we can integrate our insights with our data, linking the reflections we make with the segments of data - in whatever form, from whatever source - that prompted them. If you asked me what the main benefit is of using a dedicated CAQDAS package this would be it. Being able to treat our insights about data as data, and access them independently of, as well as integrated with, all our materials is a level of closeness that simply isn't possible when the tactics we use for analysis are highlighter pens, scissors, blu-tac, and thread.
In my next post I'll take a specific analytic task and illustrate how CAQDAS tools can bring us closer...

Oct 05, 2016 Arrow1 Down Reply
Steve Wright

Good article, thanks fo sharing.

It prompted some thinking, reflections from my own practice, teaching and consulting which is that "closeness' vs "distance" can be a false dichotomy that masks other things.

Close or immersed?
These two terms are often used interchangeably yet I would suggest they are rather different. In my current small research project on CAQDAS use 9and non-use) one non-CAQDAS user talked about highly technologically-mediated immersion. She took her recordings and listened to them in the car, on her iPod and listened and listened. Then only transcribed certain segments. I've tried this - listening to a whole interview in the car while driving is a very different experience from listening to it through CAQDAS software - but it's not about closeness it's about immersion vs distraction. QDA software has so many hooks, invitations and options for breaking up the flow of attention and immersion. If you're driving you're driving, you have no choice but to listen to the whole interview and turn your atteniton to what you can - your attention is mediated but the opportunities to interrupt that engagement are different. You can make notes at the end when you stop. The same is true with an iPod - however you might pause it and make notes more often. I felt "closer" to my data after listening to a load of interviews in the car but this was about attention and a lack of options. So in that way i can see a legitimate criticism that QDA software presents you with a lot of option to interfere with listening and immersion and this is then regarded as "distancing".

CONVERSELY when working with transcribed audio QDA software facilitates far, far greater closeness to the data by enabling synchronising the transcript with the audio - talk is no longer text but also talk. The nuances of emotion and meaning of hmmm, huh and pauses can be engaged with - you are FAR closer than with tactile printed, but soundless transcripts.

So to me it is not about the software determining this, but their interfaces are powerful mediators. The ever-present opportunities for endless organisation and re-organisation, inclusion and addition, management and noting, clicking and dragging can be distractions that are branded as "distancing".

A solution? Well wouldn't it be lovely to see some software take some cues from something like Scrivener with it's fantastic "Composition" mode (see ) to support just simple uninterrupted engagement with one activity rather than always having all the other available controls on screen begging for attention.Scrivener *really* attended to the task of writing (rather than word processing) and built around that, so there is perhaps a place for QDA software interfaces that are designed around the experience and needs of immersive analytic activities rather than software features?


So often I have attended training courses and wondered what I was doing there, feeling my life slip away into oblivion while I could be doing other more useful and interesting activities such as watching iron rust or paint flake. However, Christina's was superb. It was exactly what I had hoped for. Pitched at precisely the right level and presented in a very clear, engaging way. Being able to spend time having some real content and context given by someone who really understands the software and researcher's needs, along with a sensible amount of time to try things out and get help was great. I'm much more confident about getting to grips with my data now.
Paul Rause
Interdisciplinary researcher, Southampton University