Troubleshooting or Trouble? When Research Tools Fail

By Elizabeth Stregger
Mount Allison University Library

Spoiler alert: by the end of this story, a Data and Digital Services Librarian finds joy in coding with paper.

When my research collaborator, Dr. Christiana MacDougall, asked about using RQDA (R package for Qualitative Data Analysis) to analyze our data, I was enthusiastic. Open source software, a different way to use R, and yes, it was listed on some library guides. There were detailed YouTube tutorials. I was confident that it would meet our needs.

Following the installation instructions for Mac OSX (last tested in June 2016) was not immediately successful. I found some helpful advice on GitHub (Kopf, 2014) and installed RQDA on the three computers we use most frequently, all Macs. Our first impression was that the interface was a bit clunky and slow. We could cope with it. After all, we’d said we would use RQDA in our Data Management Plan, and installing it had been quite a lot of work. I thought we were on track.

Then we started coding. The system lagged, making it very hard to select text. Was it bad wifi in the coffee shop? Would it work better with a mouse? Did the file location make a difference? I was determined to find a way for this work, so that I could give other faculty members solid advice in the future.

I installed it on my work desktop computer, a Windows machine. Finally, RQDA worked as expected. At that point, I knew that my best advice for faculty members was to abandon any attempt to use RQDA on a Mac.

I did my coding using RQDA on my work computer. Christiana printed, cut, and manually sorted our data. While I was proud of trying my very best to get a system to work, I gained a lot of appreciation for analog methods. Moving strips of paper around on a wooden table is as satisfying as working on a puzzle or sorting shades of yarn into a fade.

I’m grateful that Christiana was open, curious, and patient with my persistence. In addition to good communication with your research partners, these are my recommendations for working with open source tools:
– Try using the research tools your library is promoting as open source options
– Keep an eye on how long it has been since open source tools have been tested for operating systems
– Balance user experience with your commitment to open source
– Share stories about research tools
– Contribute to open source projects if you have the skills
– Have a backup plan!

Reference

Kopf, S. (2014). Installation information for R with GTK on Windows/Mac OS. Retrieved from https://gist.github.com/sebkopf/9405675

This article gives the views of the author and not necessarily the views the Centre for Evidence Based Library and Information Practice or the University Library, University of Saskatchewan.

1 thought on “Troubleshooting or Trouble? When Research Tools Fail

  1. Having recently tried (and abandoned) using NVivo for Qualitative Analysis and instead moving to highlighting/manual grouping methods, I can totally appreciate this story!

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