PODCAST: How to be creative with data analysis

Alongside a growing interest in creative methods, researchers are increasingly exploring how to bring creativity into data analysis. But how do you strike the balance between innovation and maintaining a systematic, rigorous and ethical approach?

Jess Miles talks to Helen Kara, Dawn Mannay, and Alastair Roy, editors of The Handbook of Creative Data Analysis, about the role of creativity in research, its benefits for analysis and communication, and the anxieties and difficulties people might experience around using creative methods for the first time.

Listen to the podcast here, or on your favourite podcast platform:

Scroll down for shownotes and transcript.

Helen Kara is a researcher, author, teacher, and speaker specialising in research methods, particularly creative methods, and research ethics at We Research It Ltd. Dawn Mannay is Professor of Creative Research Methodologies at Cardiff University. Alastair Roy is Professor of Social Research at the University of Central Lancashire.

The Handbook of Creative Data Analysis edited by Helen Kara, Dawn Mannay and Alastair Roy is available on the Policy Press website. Order the EPUB here for £39.99.

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SHOWNOTES

Here are the links to some of the resources mentioned in the episode:

• Creativity in research webinar
• Creative Research Methods in Practice series
• International Creative Research Methods conference
• ‘Generating Materials’ in Using Social Theory by Sarah Whatmore
• Embodied Research Methods by Torkild Thanem and David Knights
• Epistemic Freedom in Africa: Deprovincialization and Decolonization edited by Sabelo J. Ndlovu-Gatsheni
• ‘Fabrication as ethical practice’ by Annette Markham

Timestamps:

Transcript:

(Please note this transcript is autogenerated and may have minor inaccuracies.)

Jess Miles: Creative research methods for data generation have grown over recent decades, and researchers are now keen to take a creative approach to data analysis too. My name is Jess Miles, and today on the Transforming Society podcast, I’m speaking to Helen Kara, Dawn Mannay and Alastair Roy, who are the editors of ‘The Handbook of Creative Data Analysis’. I think this might be the book about data analysis that creative researchers have been waiting for.

The book is vast, full of practical examples around how to do data analysis creatively, and includes images and photographs that bring the approach to life. There are graphic novellas, word clouds, objects, film, narrative, mosaics, emojis, poetry, stitching. I could go on. There’s a lovely quote in the intro from a paper of Dawn’s that says that this is research where imagination, questioning and uncertainty are welcomed as part of the process.

So let’s talk about this more. Welcome, Helen, Dawn and Ali. So excited to talk to you today and thank you for taking some time to chat. So let’s start by talking about how the book came about. It would be great to hear a bit about each of you, that Policy Press webinar and bringing the book together. Don’t know if you want to go first, Helen?

Helen Kara: Yeah, I’m happy to start on this one because I first wanted to do this book in I think 2016, my book on creative research methods, first edition, came out in 2015, and I quickly realized that we needed a book on data analysis. But I knew it wasn’t one I could write, and I didn’t even think it was one I could edit on my own well enough to make the book as good as it needed to be, and I applied for some funding from Leverhulme to see if that would support it.

But I wasn’t successful and I thought about people who could co edit with me, but I didn’t have any good ideas. But then, as you say, there was the Policy Press webinar in I think February 2021, which we did, the three of us together, me, Dawn and Ali and I already knew Dawn and I already knew Ali. So we weren’t strangers to each other.

I can’t remember if you two knew each other. Did you know each other before we started this work? No you didn’t. You do now. And in the webinar, we were, I was struck by the number of questions we got about doing creative data analysis, and we dealt with them well I think in the webinar and after the webinar, I thought, I wonder if I wonder if those guys would do this book with me that I’ve been wanting to do, because I think if we could all do it together, that would work.

And then I thought, oh, they’re really busy academics, there’s probably no point even asking. And then I thought, well, if you don’t ask, you don’t get and I’ll just email them. It’ll only take a minute and then they can say, no, that won’t take them long and it’ll be fine. And they both said yes. And I have loved working with these guys on this book.

It has really been what I wanted this process to be. And the outcome is ideal. I think it’s, you know, it’s excellent. I’m so happy with it. But you guys, you might want to pitch in with your parts of the story.

Alastair Roy: I’d just say that the webinar was really interesting because of the questions that we were asked. So I think in a way we were prepared to talk about our creative methods. And I think, you know, Dawn has this really nice idea that she communicates in the book about analysis being, in some ways the most invisible stage of research and the bit that receives the least attention.

And I think it was the questions, you know, about this phase of research in the webinar that, to me, brought to light that I knew this was an important stage of research, and yet I felt that I needed to give it more exploration, you know, in my own practice. And, you know, in a way, the book was an opportunity for us to do that, you know, through a whole load of, you know, different brilliant examples.

Dawn Mannay: Yeah, I think at the webinar, you sort of got this sense that people are just overwhelmed when they get to analysis. It’s sort of fine, you know, you’re going to go out and produce data and that’s all great, and you’re out, and then you come back with this sort of mass of stuff. And then how do you do it? And if you think about journal articles and the methods section, there might be like two sentences on analysis.

So it’s so invisible for people. So you could sort of, you know it anyway because this happens with PhD students and other researchers, analysis is always this sort of hump in the journey. And you could sort of feel that people were struggling with it. And I think I felt a bit guilty because, as Ali said, we were all happy to talk about, yeah, we go out in the field and we use all these exciting methods, but that’s not what people wanted to know about, because I think there’s a lot of books that do that really clearly and people feel more supported.

So it was great then when Helen said about, you know, doing this book together. So I felt like, you know, I could’ve come to that webinar and we could we listened to what they said and what they wanted. So that was, it was great to have this book.

HK: And then what was also good was we originally envisaged a normal sized edited collection with maybe a dozen chapters, but then we got around 60 proposals, most of which were excellent, and we thought, we can’t just pick a dozen out of these. They’re too good. And we asked, Policy Press, please, could we do a handbook because we’ve got such the, you know, the creative methods community responded to our call so positively and so helpfully, and we ended up choosing 29.

So about half of the proposals, it was difficult to make those choices. I mean, there were there was a very small number that we all said, no, that that doesn’t fit, but we probably could have picked most of them really. But then what we did was if we had say we had three on poetic analysis, we kind of pick the best one out of the three, or the one that we thought would be most appropriate for the book.

And we found other homes for some of the contributions that came to us. So I do feel that what we’ve got is really high quality, and we have to acknowledge and honor our contributors for that, because without their amazing contributions, we wouldn’t have such a brilliant book.

JM: They really are amazing contributions, and I’m really glad that you pushed for it to be a handbook, because I feel like to see all those different approaches in one book really makes you realize, like the options that are available and the ways of thinking that are possible. And I think to have had like maybe ten contributions, you wouldn’t quite have got that sense of excitement with it.

So as I said in the intro, I think interest in creative research methods has been growing like you’ve said as well. And bringing creativity to data analysis is a logical next step, and what people were calling for really. So why do you think creativity matters in research and then in data analysis in particular? Dawn, I don’t know if you want to speak to this first.

DM: Yeah, I think sort of creativity in general has always been important in my research, because I think as a researcher you might do a literature review or you might know that area or know the people that you’re working with, and then you go in with a lot of assumptions about which questions to ask, what’s important. And I think when you’ve got space for creativity, that takes the research in different directions.

So if you ask participants to produce things and generate data in different ways, it takes you to lots of questions you wouldn’t have even thought of asking. So that’s what really attracted me first to working with creative methods. And then I use a lot of creative methods to produce data. I use photographs and drawings and sandboxing and collage.

And then later I started using creative methods to get the messages out for research, because I started to think that, you know, when you do a literature review and the problems that you’ll find in your research were there 20 years ago and 30 years ago, nothing’s changing. It’s because people in practice and policy and lots of different roles, like teachers or social workers, are just not getting access to those findings because they’re in some, you know, hard to read, inaccessible language journal article that you might have to pay to download, or a long report.

So I started then doing sort of short films and music videos and artworks and posters and thought about how the creativity really works at that stage but I wouldn’t see myself as a creative analysis person. But I’ve learned a lot from editing the book about how to be more creative in that stage. So I think we all learned a lot about analyzing data more creatively.

So that’s sort of slotting now into, into my practice.

JM: And that’s great that you’ve learned from it as well. Yeah, sorry Ali.

AR: Yeah, no, sorry. I mean, I just wanted to reinforce that point that, you know, I think as editors, we probably learned so much from this. It’s a real you know, it’s a real pleasure and a real privilege, you know, to learn and in a way that that’s what we hope the book will do for other people is to give the opportunity to learn from other people’s examples.

I mean, in terms of, you know, why is creativity important in analysis? I mean, I think Dawn has, you’ve been told the important bits of the story. I mean, I always like Derrida’s idea that something important is lost by the sorts of methodological rigor that masters every surprise in advance. Or actually, I prefer Abraham Maslow, who said that to the man with a hammer.

Everything looks like a nail. And, you know, I think this is the kind of issue that, you know, creativity gets to the heart of in, in analysis is that we can all have prescribed ways of doing things that we’ve learned by, you know, working in a particular field or, you know, working in a particular discipline. But much as they have, you know, defined benefits, they also have limitations.

And so, you know, introducing different ways of approaching even the same data set, you know, generates different ideas, you know, and sometimes analysis appears as this sort of technical, rational bit of the process in which we kind of process things. But actually it’s a process of thinking with and through our data, and introducing different ways of approaching, and reapproaching, you know, our data generates different questions and different ideas and, you know, different solutions.

And I think it’s really easy to see this in some of the kind of brilliant examples in the book.

JM: It’s easy, like even if you’re doing like qualitative research, to do like thematic analysis on text from interviews, you just assume that that’s what you’re going to do to some extent, doesn’t it? Like someone doing research like very early on. It’s like you just take for granted, you’ll put it into in vivo and you’ll analyze it in that way and you don’t have to.

And maybe more interesting things would emerge if you didn’t or if you did both. Did you have anything to add to that, Helen?

HK: Yeah, I think in a way, creative methods are the bacon sandwich of the positivist hangover. And we’re getting to the point where we’re going, we’re actually moving, looping back to, I think, probably where people used to be with this sort of a process before positivism arrived and, and instituted lots of rules and, and the creative approaches to research, can still be very I mean, one of the questions we asked all our contributors was, how do you work systematically with your creative methods?

Because working systematically is important because it helps us to mitigate our biases. But how you work systematically can vary, and you can be creative with that. And I think research is inherently a creative process. And we kind of lost that for a while. It became very prescribed and rule bound and and there was the whole hierarchy of methods thing, which I have no time for, because I think the methods we choose need to be the ones that are most likely in the specific situation, and context we’re in, to help us answer our research questions, and sometimes that will be a randomized controlled trial.

It’s an excellent method in some contexts, but it’s not very useful for real world research. And that’s where creative methods really come in. And also because creativity and ethics rather go hand in hand. And we don’t have any evidence yet that doing analysis more creatively makes our work more ethical. But we do know that conventional analytic work can be very unethical.

The work of Retraction Watch has shown us that over and over again, and it seems to me that researchers who are working creatively do tend to think more carefully about ethics. And that was another thing we asked our contributors to, to reflect on the ethical aspects of their methods and to include that in their chapters. So there are some nice consistencies through the book, as well as the lovely differences of all the different approaches.

JM: Yeah. So to bring it to the book, we’ve said there’s like this huge range of approaches. So kind of needed to be selective for this podcast just because of time. And the ones I was most curious about were like participation, embodiment and fictional narrative. So let’s start here. So with participation, you highlight that it can get lost between the research activity and the analysis.

So how does creative data analysis and co-production help with analyzing, communicating and talking about research with a wider audience? Ali?

AR: Yeah, so I mean, you know, I mean, to kind of talk about how participation gets lost in, in data analysis. I mean, I think I’d kind of tap back into Dawn’s story about how she started working creatively in the first place. And I think it’s, you know, is part of an unfolding picture, isn’t it? You know, the use of creativity in different bits of the research process.

And so I think in some ways it mirrors what’s happened in participatory research, where a lot of participation in research began in the middle, with researchers defining a, you know, a research problem, recruiting people, training in them in research, getting them to do some research and then doing the analysis themselves and writing up the findings. And in a way, it seems to me that with creativity, it’s for whatever reason it’s been inserted first in the middle, you know, as different ways of generating, I’m going to call them materials, and I’m going to use that word because it taps into language that

Sarah Whatmore uses in one of my favorite research chapters of all time, that’s called Generating Materials. And she says, you know, quite often this sort of approach to research that appears in introductory textbooks seems to mirror this idea of squirrels scurrying around, you know, collecting, you know, bits of evidence, you know, or, you know, acorns to bring them back and then, you know, feast on later on, you know, and then the, the job of analysis becomes sort of ordering the acorns.

Whereas actually, you know, what we see in the examples in this book, you know, is that there are thousands of different ways of moving from generating your materials to making sense of them, and also ways of sustaining the involvement of other people in those different bits of the process. So, you know, for me, that’s why it’s tended to get lost in the past is because that’s kind of how practice is developed.

But I think one of the really exciting things in this book is we see all sorts of ways in which that involvement of people can start at the beginning and end with the dissemination of materials, and that can lead to better forms of understanding, but also also more satisfying forms of involvement for people in research.

JM: The section on embodiment in the book is interesting and a bit like what we’ve just said about participation is that the body often gets removed in the process of data analysis, possibly a bit of a niche point, but I think it’s helpful to think about. So how does creative data analysis bring the body into play? What’s the significance of this? And can you give us some examples?

HK: Well, let me start on this one because I can say a bit generally I think that embodied data analysis is not something that’s new with this handbook. It’s been written about for example, by Torkild Thanem and David Knights in their book ‘Embodied Research Methods’, and they really talk about manual data analysis rather than digital data analysis. So they talk about spreading your data out on the floor and crawling around in it and making connections and piles and taking photos as you go.

So it’s a very, very, very literally embodied process. But I think, I mean, their book is great, and I learned a lot from it, and it actually made me laugh, which not many research methods books do. Even though I do enjoy reading them. But I think they make some slightly dodgy assumptions, for example, that everyone has enough space to spread out their data on a big floor area or a big table, and that it won’t be disturbed by pets or small children or whatever.

And second, that everyone is physically able to crawl around on the floor, which of course, not everybody is. And, a different view is taken by Laura Ellingson, not surprisingly, because she’s an amputee, one of her legs had to be amputated for medical reasons. And her view is that digital analysis is every bit as embodied because you can’t do it without your body.

This is the standard argument of all embodiment researchers, which makes sense. You cannot do research without your body. But then the question is how much attention do you want to pay to those physical sensations and emotional feelings? But I think Laura Ellingson is quite right. If you’re going to do digital analysis, you need your hand to hold the mouse, your eyes to look at the screen, your fingers on the keyboard, etc. etc. your body, sitting in the chair at the desk and all of that.

And it’s, they’re both potentially embodied practices. Another thing the embodiment, researchers say, is that all research practices are embodied, which again, is kind of unarguable. But again, the point is how much attention do you pay? And we do have some lovely examples in the book. And I know Dawn particularly wants to highlight one of them for us now.

DM: Yeah. So there’s a there’s a lovely chapter from Naomi Clarke about stitching, so it explains how she’s both a researcher and crafter, and how she embeds stitch into every stage of her research. So in her doctoral work she does, there’s this lovely bit in the chapter about how she sort of stitches a square for every participant. And in that space, then reflects on those accounts and, and has sort of moments of realization about those accounts through the stitching, through this sort of stitch representation.

So I think that chapter really speaks about the connection between hand and mind. So there’s always been this sort of the work of the mind and the work of the hand, this sort of academic work manual work. So there’s always been this sort of cut off between the two, but it shows the hand and the mind active together in that process.

And there’s another chapter, by Karen Hammond and Nick Fuller. And this is sort of clearly see the whole body involved in this. So they use shamanic tactics in their research. So going into this sort of, light trance state so someone’s drumming a rhythm and, Karen talks about sort of laying on the floor in a blanket and they burn oils so you’ve got that the senses all working together and how going into that state with an intention.

So you sort of go into the state with an intention, led to these sort of aha moments about data analysis and this sort of being able then to to reframe things and think about the value of preserving complexity and ambiguity rather than coming up with a definite outcome in that stage of data analysis. So I think those, chapters and other chapters in the book sort of counter that argument.

You know, that research is embodied in a different ways, whether it’s hand and mind or whether it’s whole body. Your senses are always involved, and your body in, in research as a whole, not just in analysis.

JM: So it’s kind of acknowledging that and embracing that, I suppose. And how does that link to creativity, presumably by stepping out of your mind a bit and trying to see things in different ways, that that’s a creative process, isn’t it? That might allow for different things to emerge.

DM: Yeah. And I suppose is creativity and reflexivity. So it’s the ways in which being creative help us be more reflexive.

JM: Yeah.

DM: I think you can do that with analysis. You see in all sort of stages of research, so if you’re doing it as a means of data generation, or if you’re doing it yourself to design a study or to reflect on research, it gives you the space that you don’t have. And that’s one of the most valuable things I think about creativity is that it slows you down.

You can think in different ways because it’s easy, we can talk really, really quickly and we can write and type but doing something creative slows you down in a different way and makes you see the world and different aspects of research through a different lens. I think.

JM: And I think I’m right, that, like researchers generally are being called to be more reflective, aren’t they? And, acknowledge their role in the process more so this, this kind of practice actually just offers really direct ways of being able to do that. So it’s useful, really useful for everyone. So I’m also interested in how fiction, drama and creative writing can contribute to research and data analysis.

And I thought this was interesting because it almost seems counterintuitive to introduce imagined elements, but also very fun and kind of giving more thing, more ways of engaging with the data. So I wondered if you could speak about that.

HK: Well, I think the role of imagination and research is absolutely key. In fact, no research project happens without a level of imagination. You have to imagine the possibility of a project before you can even apply for funding or get it off the ground. And yet, imagination is often not really discussed as important. Alison James back in 2012, Alison James put forward the idea that imagination might be particularly useful for secondary data, qualitative secondary data.

Because you don’t have the context, you need to use your imagination more because if you’ve collected your own primary data, you know how that person’s voice sounded and what the room was like that you talk to them in or the online environment and whatever, and what they were wearing and all sorts of stuff that informs your views. And if you’re working with secondary data, you don’t have any of that.

You only have a relationship with words on a page or images or whatever it might be. That’s not better or worse. It’s it’s more freeing in some ways and more limiting in others. But imagination has a has a key role in helping the data analyst to build a picture of the participants of their situations and figuring out why they say what they say.

And imagination doesn’t mean making it up. It’s like creative, systematic use of imagination. And I think one of the things in this question is not only about the role of imagination, but also the boundary between truth and fiction, because they’re not necessarily it’s not necessarily a hard boundary between truth and fiction. We tend to think of it as truth on one side and fiction on the other.

But if you think about things like memoir like travel writing and some research is going down this road to it’s what the Arts Council would call creative nonfiction. So it’s fact based but sometimes fictionalized. There’s all sorts of reasons why you might fictionalize in research. So it might be to further anonymize participants. So you might make a fictionalized composite case study, Annette Markham’s work is very useful on this.

So you might make a study with elements of different participants that add up to a whole, recognizable but not real participant. To illustrate the situations those participants might find themselves in. And, if I can do just a little side plug for a moment, in the Policy Press short book series I edit called Creative Research Methods in Practice, there’s a really good book on fiction and research by Leah Gilman and Becky Tipper.

That’s well worth having a look at. But it does play out in analysis, because sometimes it’s useful to do fictionalized work in analysis. Lisbeth Berbary used screenplay writing. She- it wasn’t to make movies, but she wrote screenplay scenes about the interactions that she perceived her participants engaging in to convey those on the page. She’d done thematic analysis already, but she felt that that wasn’t really getting getting some of the immaterial across well enough.

So she turned to writing screenplay scenes, and that worked much better. There’s all sorts of options, and in our book there are a bunch of options. There’s a whole section on creative written analysis with chapters about I poems and composite narratives developing characters that I talked about. And there are others. There’s the thing about dividing the book into sections is that virtually every chapter could have gone into at least three of the sections, so it’s a little bit artificial, but it just makes the book a bit more digestible.

I think. Does anybody want to add anything to that on how imagined elements can- go on Ali.

AR: Well, just a couple of things. I mean, I think you’re right, Helen, 100% that creativity is involved. All research involves creativity, you know, I mean, I love C. Wright Mills, who, you know, famously said, you know, that it’s the imagination that distinguishes the researcher from the mere technician. Yeah. And I mean, I mentioned before we started Les Back’s book, the Art of listening, you know, and I think sometimes analysis is almost considered as the point at which, you know, the listening stops and where we sort of process our data and, you know, mold it into a form.

And as Dawn said, sometimes this is the bit that seems to happen behind closed doors. And I think for me, data analysis needs both playfulness and vigilance. Yeah. So, you know, it’s not one or the other. You know, it’s both of those things. And I think what some of the brilliant approaches that are described in this book help us to understand is that, or help to open out for researchers, is this sort of relaxed receptivity, you know, to our data, you know, through that process of generating understandings, you know, from our materials, that open out different ways of understanding those materials and different ways in which the stories from them, you know, could be told. So I think this is implicated in all research. But what we see in the examples in this books is ways of, you know, opening out, you know, different ways of approaching the materials.

JM: We’ve mentioned things over the course of this chat, about like rigor, being systematic, vigilance. And you acknowledge in the book that it’s challenging to bring creativity into data analysis while retaining this systematic, rigorous and ethical approach. And I think there can be almost a fear of doing things that sit outside of institutional and disciplinary norms. So I thought it might be helpful to talk a little bit about the anxieties and difficulties that people might have around this, and how we can mitigate them.

AR: Should I go first on this? I mean, I love this bit of the book, you know, I must say. And, you know, I find it so helpful to kind of think with the materials. And although in a way, this book is a celebration of, you know, creative approaches to analysis, what we see in some of the examples really clearly is that creativity or creative approaches to analysis is not always welcome in certain contexts, because people are expected to work within disciplinary norms.

And so two of the examples that I love in the book are Louise Couceiro, who described entertaining the possibility that her own creative approach to data analysis might simply be a frivolous procrastination strategy. And I think that speaks just so simply and beautifully to the anxieties that can accompany choosing to do something in ways that are different from other people working in your discipline or school or, you know, department or whatever.

And another great example in the book is from Jennifer Leigh and colleagues who were working in a STEM discipline, you know, and they described how one of the main challenges for them was documenting, disseminating and justifying the analytic process in a way that was understandable and deemed rigorous enough. You know, for a scientific audience. So, you know, we really talk about this towards the end of the book in terms of transgression, you know, and that does involve a certain braveness sometimes to be able to be prepared to, you know, step outside of the kind of norms of, you know, of one’s discipline and the great news, you know, for example, with Jennifer Leigh’s colleagues is, despite their their approach, being received initially with quite a lot of suspicion, actually, when they presented their work, it receive really positive appraisals. So, you know, there’s lots of kind of good news stories, but realistic stories about this in the book.

JM: Do you think it is generally more well received than we might think it will be? Creative approaches in research?

HK: I think it still varies. My own view is that there are some people who are still quite, still think creative methods are like fluffy, girly playing, not proper research. And my view is that those people are dinosaurs and they will die out. We just have to wait a little while. And generally I think I have seen I mean, I’ve been working on creative methods for ten years now, and I have seen acceptance levels improve dramatically during that time.

We’re not 100% there yet, but we’re getting a lot closer. And I’ve even had, you know, government departments getting in touch saying, can you come and tell us about this creative research business? Because we think we need to know, though that’s an indication- they don’t pay me. So I don’t go, but at least they’re asking the questions. And that’s a real indication because governments are often very small c conservative about how they do things like research.

So I think that’s, that’s really positive. It’s different in different parts of the world though. And I think we do need to make that clear, because in some parts of the world, creative methods are much less acceptable. I just recently read a great book, which I now I cannot remember the name of because I am old and my memory is faulty, but it was about epistemic freedom in Africa.

Let me just see if I can find it. And it was talking very much about how colonization didn’t only apply to physical, here we go. ‘Epistemic Freedom in Africa: Deprovincialization and Decolonization’ by Sabelo Ndlovu-Gatsheni. And that is an awesome book because the author talks about how people’s minds are still colonized in many places in Africa.

And I see that when I read research from Africa, it’s often very sort of like stuff that was being produced here in the early 80s, in that- at the height of the Paradigm Wars, it’s very positivist focused. I’ve actually just been asked to the first ever qualitative research conference on African soil, which, if they get the funding, will happen next October in South Africa, which will be really exciting.

But that’s an indication that, in that continent, qualitative research is, you know, new and happening. And actually there’s a lot of creative research is done in Africa, but it’s often done by indigenous researchers who don’t tend to publish so much. And if they do, it’s probably not in English, which is fair enough, because why should it be?

So, I think we need to acknowledge that what we’re talking about here is in our specific cultural setting and doesn’t necessarily apply in the same way, although I think there are a lot of people who wish it did, and it I think will in the end.

JM: That’s a really important point to mention, isn’t it. Dawn?

DM: Yeah. And I think there is a lot more acceptance than, you know, since probably we’ve all noticed since we first started using creative methodologies, there has been a definite shift and people have been able to achieve great things with embedding creativity throughout their research. So earlier, Ali was talking about sort of participatory methods and Jessica Mannion’s chapter.

So she works with the Relationships and Sexuality Research team as co-researchers and they’re involved in the design, data generation, a very long process of analysis and then dissemination. But I think the real danger with this is even when you have acceptance, you still need time. So there’s pressure on researchers to meet deadlines. So there’s ways that we’d like to work in and we think are more creative or more ethical. But we can’t always do it. So I think I also don’t want readers to read the book and feel guilty and think, oh, I’m not doing it properly, I could have done it longer. I could have involved participants. I could’ve been more creative. Because even when you have acceptance from institutions or funding organizations, people also want findings in deadlines, which mean that you can’t work in the creative way that you would like to.

So I think it’s not just about the acceptance that creative methods can be a good thing, and involving participants at all stages of the research can also be a good thing, but it’s institutions and funding bodies funding adequately to enable time. Because if you haven’t got time, yeah, your creativity is always limited.

JM: Yeah, yeah, it’s really true. I was also just thinking as you were speaking and I think you say it in the book as well, just for those who do want to use more creative methods, just the very fact of having this handbook to cite and reference kind of gives a bit of permission to do it. You do say that in the book and gives confidence as well.

DM: Yeah. And I say that to students. A lot of people contact me. I’ve had I’ve been meeting people like every week this month, I think, who’ve just sort of emailed and said, oh, hello, can you have a chat about creative methods? And particularly when it’s in a discipline or a field where it’s not usually used, and I’m sort of saying, okay, you can say it’s been used successfully here. It was used in this study. And, you know, this study had an influence or there’s an impact case study from this work. So you can make a evidence based argument in a field where evidence based arguments are needed to justify your methods. So I think that’s really good. And yeah, this book will help with this as well, I think.

HK: I think it will and in that context, I was particularly pleased that the first section of the book is headed the creative analysis of quantitative data, because I think it’s really important for people. This is across all disciplines. You know, I teach creative research methods generally to doctoral students in universities around the place, and I get people from all disciplines.

I’ve had people from, you know, computer science and dance and law and sociology and art and physics and, you know, the lot. And it’s it’s fascinating stuff, I think, because it is it’s just expanding so much.

JM: Yeah. And that it’s just different that different ways of seeing different lenses is really so important isn’t it, in all areas. So I have one more question for all of you. And it kind of I think we’ve spoken a bit about it already, but it’s really just what do you want people to take away from the book? And what would you say to people who are considering using creative methods? Maybe for the first time. Do you want to go first Ali?

AR: So for me, one thing I really like about the book is that we asked all of the authors to explain their approach in sufficient detail that someone else could run with it, and I think that everybody’s done that, and that makes it for me a really usable book. And I’m really, you know, I’m really proud of that. And I really thank, you know, all of the authors for, for running with that, you know, because I think that means that people can dip in to different chapters and sync with other people’s ideas, because quite often in research, we’re not just borrowing someone’s approach as a whole.

You know, we’re we’re thinking how we can, you know, take elements or bits, but, you know, yeah, I think it’s it’s usability that I really like.

HK: I think there’s a there’s a few things there. I mean, it’s a sort of double question. People who are considering using creative methods for the first time, I’d say give it a go. What have you got to lose? If it doesn’t work out, you’ll have learned something. If it does work out, you’ll have learned something. So, and I agree with Ali that the book gives us the how that we didn’t have it was the gap when we were doing that webinar in 2021, we had some answers for people, but I kind of felt and I think you too both also felt, that our answers weren’t really enough, that you know that clearly more was needed.

And now we’ve got what is very much needed. And something I think that’s interesting is there’s a there’s a few sort of overall learning points. There are five of them. We’ve already touched on a couple. Jess already said that analysis, it’s not a discrete phase of research which falls between getting your data and then, you know, writing up your results.

And the book really demonstrates that analytic work begins when you’re designing your research and it continues all the way through dissemination and beyond, because we’re analytic pattern recognizing beings, and we’re doing that processing all the way through. And another thing is that any data can be creatively analyzed, whether it’s quantitative or qualitative or both, whether it’s been collected in conventional or creative ways, doesn’t matter.

Any data, whether it’s primary or secondary, you can, you analyze it creatively if you want to. Then it’s really clear to me from the chapters that doing analysis differently helps us to find new insights, new learning, new understandings. And I know that when we were reading the draft chapters and I felt so privileged to get to read these chapters before anybody else apart from you two.

And we’d be meetings and be like, I want to try that method. I want to try this one. Oh, I want to try that one out. And there’s some really. And it’s not just about being seduced by a sexy method, because clearly that’s not great practice. But these methods are just so interesting in what they can afford to us as researchers for our practice in terms of new insights, new learnings, and new understandings.

It’s also really clear from the book that analyzing data often requires creativity, whether or not that is explicit, that applies to conventional research as well as creative research, it’s interpretative, analytic work is, to an extent a creative process, perhaps not so much if you’re doing pure quant work where you’ve got clearly statistical calculations you can use to, you know, find your results.

But what fascinated me, and I’ve known for a while that researchers use tacit creative practices to support their analytic work, as well as acknowledged creative practices. But several of our contributors highlighted these. I mean, I myself use poems, very bad poems, but they help me and diagrams when I get stuck in the analytic fog. And I think, oh, you know, every single research project this happens, I get to a point.

I think none of this is ever going to make sense. The fraud police are definitely going to be knocking on my door this time. You know, I can’t do this. I don’t know why I ever thought I could for the last 25 years and I’ve, I’ve never I’ve never really before this talked much about how I use poetry and diagrams, but I was really interested to discover other tacit creative practices people use.

People use visual arts practices like doodling, drawing, collage just in their own time, in their own analytic process. People do making, they make models, installations, crafty fabricy things, all sorts of stuff. Music is used often to accompany and promote thought, whether that’s playing music or listening to recorded music, and other embodied practices like walking, running and swimming.

I’ve often thought that going for a walk is helpful if I’m a bit stuck in my thoughts, you know it can unstick you. But people are using those processes very purposely for their analytic work. No doubt there are other options as well. And the fifth and final overall learning point again, we’ve touched on this. Analytic processes do need to be systematic, but they don’t need to be rigid.

They don’t need to be fixed. The book demonstrates in so many ways that analytic work can be experimental, as Ali said, playful and fun. And why should research not be fun where it can be? Why should it always be so serious and po faced? I don’t think it should. I fully agree with Ali that yes, we need vigilance and we also need playfulness.

So I think those are the things, some of the things I would like people to take away from the book, I don’t know, what do you want to- do you want to add anything to that, Dawn?

DM: Yeah. I mean, I think this book is going to be a great starting place for readers, us included as readers, you know. So each chapters being carefully written so the reader can see exactly what was done. So I think that’s going to be a lovely intro for people who are thinking about, how can I bring creativity into my analysis, but I also think beyond the book, when you want to try something new, a good thing to do is to reach out to people using that method and see if they’ll have a quick chat with you.

Go into those spaces so you know the creative methods community are supportive. I’ve found, so if I’ve contacted people they are happy to chat through their work. People contact me, I’m happy to have a chat. I know that Helen and Ali, you know, it’s the sort of same thing. People have got questions. So there is that supportive community that you can reach out to people on an individual basis and there are also lovely, safe, creative spaces.

So there’s a new conference, The International Creative Research Methods Conference, which is held in Manchester in September. And it’s so it’s so absolutely lovely honestly, I can’t, can’t think of like a sensible way to talk about it. It’s so it’s like a really safe space. So when you go there, there’s lots of different people from different disciplines talking about different aspects of creativity.

It’s very warm and friendly. You don’t get any sort of showing off or, you know, everyone’s sort of part of the same community. And a lot of people, as we were talking earlier, who feel isolated in their own institutional organization, like they’re doing something strange that shouldn’t be dabbled in, feel like they’ve found a home. So I think talking to individuals, talking to colleagues, talking to friends, and finding those safe spaces is, is really inspiring and helps you work in a creative way.

HK: And I think as well, the conference has a hybrid element. So people who cannot get to Manchester, cannot get to the UK, are able to be part of this community, although we are all in the UK and as I said before, this is to some extent culturally situated, the creative methods community is worldwide and certainly we are also have a creative research methods journal.

The first issue will be launched next year, so there’s increasing numbers of resources for the creative methods community and increasing activity within that community, and an increasing understanding of people doing creative research, that they belong to that community. And they’re part of this, this ever shifting, growing, changing community, which is lovely. And that’s been building pretty much over the last ten years.

I think we had the first Creative Research Methods conference in May 2016. I think it was in the, at the British Library. So that’s actually only about eight and a half years. But, that was the first time I know that the that something like that community came together. Ali I think you were at that one, weren’t you?

Yeah. So yeah, it’s really exciting to be part of this and to see the community spreading its wings and learning to fly.

JM: It’s so exciting. It feels like such a moment. Thank you all so much for talking to us today. The Handbook of Creative Data Analysis is edited by Helen Kara, Dawn Mannay and Ali Roy is published by Policy Press and available on our website, which is policy.bristoluniversitypress. co.uk. Don’t forget, you can get 25% of all our books by signing up to our mailing list.

And thank you for listening. If you’ve enjoyed this episode, please follow us wherever you get your podcasts. And most importantly, thank you, Helen, Ali, and Dawn for creating this amazing book that I really think will make a difference to people doing research and data analysis.

DM: Thank you Jess, and thanks to all our contributors too.

HK: Yeah, all of our lovely contributors. We could not have done this without them and they were all so lovely to work with. Every single last one.

JM: Thank you.