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Develop your visual literacy with NVivo diagrams

27 July 2017 - BY Kath McNiff

If you spend time any time reading through journal articles about qualitative research, you could be forgiven for thinking that academics have something against visual displays. Sure, you might spot the odd bar chart or Venn diagram but that’s about it.

In a recent paper, visualisation experts (Scagnolli &Verdinelli) interviewed the editors of leading qualitative research journals to find out why visuals are so “under-utilized and under-developed”.

It turns out, that although editors are in favour of visuals and agree on how useful they are, authors are often hesitant to include them. Scagnolli & Verdinelli point to a combination of factors to explain this; journals don’t give clear enough guidelines for visuals and qual researchers receive little formal education in how to use and create them.

Unlike researchers in other more quant-based disciplines (like business and science), qualitative researchers are unsure about using visuals to express their ideas – words are a much safer option. This is a shame because they miss out on opportunities for deep thinking and compelling story-telling.

This post looks at how qualitative researchers can build confidence and develop their ‘visual literacy’ by experimenting with diagrams in NVivo.

Why focus on diagrams?

NVivo provides all sorts of tools for visualizing your data. You can brainstorm with mind maps or demonstrate frequencies in a chart. You can cross-tabulate your themes in a matrix or explore terminology in a word cloud or word tree.

This post focuses on diagrams because they offer an easy-to-use yet powerful way to detect underlying patterns and connections in your data so that you can move beyond a laundry list of themes to deliver findings that add real value to your field of research.

Diagrams (and other visualizations) also support what Pat Bazeley calls the analytical cycle of Describe, Compare and Relate – a tried and true formula for enriching your analysis. Pat explains this approach and gives great advice about visualizing your data in her book, Qualitative Data Analysis: Practical Strategies.

You should start experimenting with diagrams early in your project – so that visualizing becomes a habit just like journaling and memo writing.

Explore Connections, Patterns and Relationships

Once you’ve done some preliminary coding, you can use an Explore diagram to follow the connections and paths that are beginning to take shape in your data.

For example, you could select an interview transcript and right-click to create an Explore Diagram:


An Explore diagram with an interview transcript and it’s connected items

NVivo automatically displays the themes and other items connected to the interview.

The diagram provides a holistic picture of how an interview has contributed to your growing knowledge and can act as a launching point for further investigation.

For example, in the above diagram, you may want to explore the theme of Real Estate Development – just right click on the node and choose Change Focus:



An Explore diagram with a node at the centre

Now, Real Estate Development is at the centre of the diagram and you can see all the other interviews that have been coded at this theme. You can also see connections to material in PDF articles and social media datasets. From this, you can start to build a story around the theme of Real Estate Development.

You can step forward and back through the diagram history as you explore the connections between items.

If you decide to use the Explore diagram in your dissertation or journal article, just right-click and choose Export Diagram.

After you finish coding an interview or article, get in the habit of visualizing the results. This can help you consolidate your thinking – particularly if you’re working in a team.

When you’re writing-up your notes in a memo, you can copy and paste the visualization as a record of your progress.

Compare people, places and themes

You can also use diagrams to make comparisons.

Comparison can have a ‘wow’ factor, the power to surprise and excite your interest, to set your brain racing. (Bazeley, 2013, p. 255).

In NVivo, you can generate a comparison diagram to compare two of the same type of project items—for example, sources, nodes or cases—to see their similarities and differences.

This is a great way to uncover patterns and flush out inconsistencies.

For example, this diagram compares the cases for two interview participants called Helen and Paul.


A diagram comparing the coding of two interview participants

Both Helen and Paul talk about Economy and Jobs – so it might be interesting to review the themes in context to see if they share common views.

Helen comments on Real Estate development but Paul does not – are there reasons for this? Maybe age, gender or location have something to do with it? You could go on to explore the options using a Matrix coding query.

This video can help you get started with Explore diagrams and Comparison diagrams.


Cluster to find commonalities and outliers

Cluster analysis diagrams give you another way to see the patterns in your data by grouping sources or nodes that share similar words, similar attribute values, or are coded similarly by nodes.  

This can help you to see commonalities and identify outliers.

For example, you could do a cluster analysis on your coded interview transcripts:


Cluster diagram based on how interviews transcripts are coded

In this diagram, you can see that the interviews for Robert, Susan and Thomas and William are clustered together – maybe these participants are interested in similar themes? Is this because they live in the same community or maybe because they’re new to the area?

Meanwhile, Helen’s interview stands out as being different. This could be because she has a unique perspective or because the transcript was coded by a different researcher – either way, it opens the door to further investigation!

You could also try clustering articles from a literature review or clustering participants based on their demographic attributes.

Practice your visual skills at every stage

The more you practice visual techniques throughout your analysis, the more comfortable you’ll be using them to illuminate your findings in a thesis or journal article.

Don’t be afraid to experiment with the diagrams and other visualizations in NVivo – it’s a safe space to learn by trial and error.

Visual literacy gives you an edge. It informs and enriches your analytical process and it makes your work stand out in the text-heavy crowd.

Are you a fan of great visuals? Do you use them in your own work? How did you develop your visual skills?

So many questions! Feel free to answer any of them in the comments below.


Scagnoli, N. I., & Verdinelli, S. (2017). Editors’ Perspective on the Use of Visual Displays in Qualitative Studies. The Qualitative Report22(7), 1945-1963. Retrieved from http://nsuworks.nova.edu/tqr/vol22/iss7/13

Bazeley, Patricia. (2013) Qualitative Data Analysis: Practical Strategies. SAGE Publications. Kindle Edition.