A review of Taguette – an open source alternative for qualitative data coding

taguette logo

Motivation and context

As you might know, I’m currently undertaking a PhD program at Australian National University’s School of Cybernetics, looking at voice dataset documentation practices, and what we might be able to improve about them to reduce statistical and experienced bias in voice technologies like speech recognition and wake words. As part of this journey, I’ve learned an array of new research methods – surveys, interviews, ethics approaches, literature review and so on. I’m now embarking on some early qualitative data analysis.

The default tool in the qualitative data analysis space is NVIVO, made by Melbourne-based company, QSR. However, NVIVO has both a steep learning curve and a hefty price tag. I’m lucky enough that this pricing is abstracted away from me – ANU provides NVIVO for free to HDR students and staff – but reports suggest that the enterprise licensing starts at around $USD 85 per user. NVIVO operates predominantly as a desktop-based pieces of software and is only available for Mac or Windows. My preferred operating system is Linux – as that is what my academic writing toolchain based on LaTeX, Atom and Pandoc – is based on – and I wanted to see if there was a tool with equivalent functionality that aligned with this toolchain.

About Taguette

Taguette is a BSD-3 licensed qualitative coding tool, positioned as an alternative to NVIVO. It’s written by a small team of library specialists and software developers, based in New York. The developers are very clear about their motivation in creating Taguette;

Qualitative methods generate rich, detailed research materials that leave individuals’ perspectives intact as well as provide multiple contexts for understanding the phenomenon under study. Qualitative methods are used in a wide range of fields, such as anthropology, education, nursing, psychology, sociology, and marketing. Qualitative data has a similarly wide range: observations, interviews, documents, audiovisual materials, and more. However – the software options for qualitative researchers are either far too expensive, don’t allow for the seminal method of highlighting and tagging materials, or actually perform quantitative analysis, just on text. It’s not right or fair that qualitative researchers without massive research funds cannot afford the basic software to do their research. So, to bolster a fair and equitable entry into qualitative methods, we’ve made Taguette!

Taguette.org website, “About” page

This motivation spoke to me, and aligned with my own interest in free and open source software.

Running Taguette and identifying its limitations

For reproduceability, I ran Taguette version 1.1.1 on Ubuntu 20.04 LTS with Python 3.8.10

Taguette can be run in the cloud, and the website provides a demo server so that you can explore the cloud offering. However, I was more interested in the locally-hosted option, which runs on a combination of python, calibre, and I believe sqlite as the database backend, with SQLAlchemy for mappings. The install instructions recommend running Taguette in a virtual environment, and this worked well for me – presumably running the binary from the command line spawns a flask– or gunicorn– type web application, which you can then access in your browser. This locally hosted feature was super helpful for me, as my ethics protocol has restrictions on what cloud services I could use.

To try Taguette, I first created a project, then uploaded a Word document in docx format, and began highlighting. This was smooth and seamless. However, I soon ran into my first limitation. My coding approach is to use nested codes. Taguette has no functionality for nested codes, and no concomitant functionality for “rolling up” nested codes. This was a major blocker for me.

However, I was impressed that I could add tags in multiple languages, including non-Latin orthographies, such as Japanese and Arabic. Presumably, although I didn’t check this, Taguette uses Unicode under the hood – so it’s foreseeable that you could use emojis as tags as well, which might be useful for researchers of social media.

Taguette has no statistical analysis tools built in, such as word frequency distributions, clustering or other corpus-type methods. While these weren’t as important for me at this stage of my research, they are functions that I envisage using in the future.

Taguette’s CodeBook export and import functions work really well, and I was impressed with the range of formats that could be imported or exported.

What I would like Taguette to do in the future

I really need nested tags that have aggregation functionality for Taguette to be a a viable software tool for my qualitative data analysis – this is a high priority feature, followed by statistical analysis tools.

Some thoughts on the broader academic software ecosystem

Even though I won’t be adopting Taguette, I admire and respect the vision it has – to free qualitative researchers from being anchored to expensive, limiting tools. While I’m fortunate enough to be afforded an NVIVO license, many smaller, less wealthy or less research-intensive universities will struggle to provide a license seat for all qualitative researchers.

This is another manifestation of universities becoming increasingly beholden to large software manufacturers, rather than having in-house capabilities to produce and manage software that directly adds value to a university’s core capability of generating new knowledge. We’ve seen it in academic journals – with companies like EBSCO, Sage and Elsevier intermediating the publication of journals, hording copyrights to articles and collecting a tidy profit in the process – and we’re increasingly seeing it in academic software. Learning Management Systems such as Desire2Learn and Blackboard are now prohibitively expensive, while open source alternatives such as Moodle still require skilled (and therefore expensive) staff to be maintained and integrated – a challenge when universities are shedding staff in the post-COVID era.

Moreover, tools like NVIVO are imbricated in other structures which reinforce their dominance. University HDR training courses and resource guides are devoted to software tools which are in common use. Additionally, supervisors and senior academics are likely to use the dominant software, and so are in an influential position to recommend its use to their students. This support infrastructure reinforces their dominance by ascribing them a special, or reified status within the institution. At a broader level, even though open source has become a dominant business model, the advocacy behind free and open source software (FOSS) appears to be waning; open source is now the mainstream, and it no longer requires a rebel army of misfits, nerds and outliers (myself included) to be its flag-bearers. This begs the question – who advocates for FOSS within the academy? And more importantly – what influence do they have compared with a slick marketing and sales effort from a global multi-national? I’m reminded here of Eben Moglen’s wise words at linux.conf.au 2015 in Auckland in the context of opposing patent trolls through collective efforts – “freedom itself depends upon how we make use of the technologies we are creating”. That is, universities themselves have created the dependence on academic technologies which now restrict them.

There is hope, however. Platforms like ArXiv – the free distribution service and open access archive for nearly two million pre-prints in mathematics, computer science and other (primarily quant) fields – are starting to challenge the status quo. For example, the Australian Research Council recently overturned their prohibition on the citation of pre-prints in competitive grant applications.

Imagine if universities combined their resources – like they have done with ArXiv – to provide an open source qualitative coding tool, locally hosted, and accessible to everyone. In the words of Freire,

“Reading is not walking on the words; it’s grasping the soul of them.”

Paulo Freire, Pedagogy of the Oppressed

Qualitative analysis tools allow us to grasp the soul of the artefacts we create through research; and that ability should be afforded to everyone – not just those that can afford it.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.