Creating poetry from data to aid analysis

Poetry is an incredibly versatile medium for anybody working with qualitative data sets to consider adding to their toolkit. As well as helping solve problems, poetry can also be used as a lens through which to re-analyse data, presenting this analysis in a unique and accessible manner. Poetic transcription is one such method that enables both researchers and students to see their data anew.

Poetic transcription was first presented as an experimental form of writing by the qualitative researcher Corrine Glesne, who defined the process as the creation of poem-like compositions from the words of interviewees. To demonstrate this process, Glesne used interviews conducted with Dona Juana, an elderly Puerto Rican researcher and educator, creating poetry that gave voice to Dona Juana in her own words.

As this research method has evolved, it has become clear there are many different ways in which poetic transcription can be used as a process to analyse and reassemble data. The method I present here is a simplified and practical process that can be applied to almost any qualitative data set, such as surveys, field notes or interviews.

Step 1: Identify 15 to 20 illustrative lines.

Having first familiarised yourself with your data (i.e. by reading it through several times), identify 15 to 20 lines that are representative of the overall narrative(s) or theme(s).

After you have identified these lines, write them sequentially, one on top of another. This is the initial poem with which you will be working.  

Step 2: Assess the rhythm of the piece.

Definitions of what does and does not constitute a poem are long and storied. However, I think that overly restrictive definitions can be exclusionary, and as such I offer the following inclusive, and some might say very loose, definition: all poems have rhythm.

With this definition in mind, read through your initial poem, both out loud and in your head. Where does rhythm occur? Where is it absent? Are there any lines that might benefit from repetition? Are there any lines that do not fit?

Step 3: Add and remove lines.

Edit your poem to address these rhythmical observations. For me personally, I believe that this precludes the addition of any words that do not appear in the data you are analysing. It is also important for any identifiable information to be removed at this stage. Such identifying information may either be explicit (such as name and job title), or implicit (such as personal history or favoured phrase).

Read through your data again; are there any other lines you can add to your poem? These lines must add to the rhythm but must also preserve the overall interpretation of the piece.

Step 4: Share.

Now that you have a non-identifiable piece of rhythm, it is time to share it. Acknowledging that the “final” poem that you produce, prior to sharing it with others, is not necessarily the final evolution of the poem affords both you and others an opportunity to revisit the poem and its potential impact. For example, if you are using data that has been obtained via social media then you could share it with members of that online community.

Some sense of belonging

To show what this looks like in practice, I now present a transcribed poem that was created via this process, using verbatim responses to an equality impact assessment for the Digital Support ​Partnership (DSP) Project at Edinburgh Napier University. The purpose of the DSP was to assess and develop key lessons from the impact of Covid-19 on digital support across the university’s teaching and learning services for both staff and students.

Working off campus has broken a routine
more opportunities to attend online sessions
in relation to any number of issues and realities,
greater flexibility and understanding.

Working off campus has broken a routine
I have found it easier to manage my condition
it is easier to manage pain and fatigue,
and I am in a better state of mind becau­se of it.

Working off campus has broken a routine
it has actually improved
my ability to communicate with others,
as they are easier to get in touch with.

Working off campus has broken a routine
it made meetings more democratic as it was
now more difficult for dominant personalities,
to talk over other participants.

Working off campus has broken a routine
it has led to improvements in online educational
experience and enabled communication,
with students outside Edinburgh.

Working off campus has broken a routine
I have experienced genuine collegiality
and community during lock-down,
I feel we all came together.

Working off campus has broken a routine
I have seen the efforts of a lot of amazing people
trying their hardest to perform a difficult job,
under far from ideal conditions.

Working off campus has broken a routine
my plea is to pause on that
and allow us to re-connect in person,
to the sense of belonging we had.

There are many challenges we need to address, but as the lines in this poem attest to, there are also opportunities we must grasp hold of, to ensure we are fully taking into consideration voices and needs from across the university.

As this example hopefully demonstrates, poetic transcription presents an alternative lens through which to view data, inviting us to hear it once more in its own, discernible voice.

Sam Illingworth is associate professor in academic practice at Edinburgh Napier University and author of Science Communication Through Poetry. His work focuses on using poetry to develop dialogue between scientists and non-scientists.

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Read more about Sam’s work focused on using poetry to communicate science.

Take part in Sam’s current research project which is using poetry to explore staff experiences of belonging in higher education.