Data Dreaming

Inspired by my last post on What is data?, a researcher – who needs to remain anonymous – has written this guest post for my blog.

As an interdisciplinary researcher working in arts/health/humanities contexts, I am interested in the language used to discuss data: terms such as ‘rich’ and ‘noisy’ refer to ‘evidence’ that is complex or messy. Data can take many forms as Helen Kara’s blog (and books) articulate, and can also carry different values. The power practices played out between qualitative and quantitative research paradigms are also evident in the history of arts-based practice research as a poor relation to written outputs. We are on a long journey towards recognition and understanding of arts paradigms in terms of audits, funding and, most importantly, knowledge.

Last Thursday (17 March 2022), academics in receipt of grants from UK research councils were busy submitting their annual outputs to ‘Research Fish’, a reporting system for the outputs of grant funded projects. The research leads are required to complete online forms with details of all the material that has been produced that is associated with the grant. Reports are required while the research is ongoing and for five years after funding has ended. For arts-based researchers, this exercise can feel like a process of putting a square peg in a round hole due to the scientific bias of the reporting format and categories. Even the section on the impact narrative seems to offer limited opportunity to discuss how research can positively impact on individuals; I found myself ticking the ‘other’ box rather too frequently after wrestling with the different categories offered on the form. I even wondered whether the timing of the Helen Kara’s blog addressing the vexed issue of ‘What is data?’ had been deliberate or a happy/unhappy accident in view of the deadline that day for the Research Fish audit.

Fishing completed, I returned to my emails to find an urgent message about one of the funded projects I’d just reported on. This research grant was in its final year and involved a team of arts practitioners facilitating creative workshops to explore questions about adolescent identities and mental health. A query had been raised by the funder during an audit of expenditure and I was informed that a consumables cost had been removed as it was deemed ineligible due to not being ‘directly related to the research being carried out’. The items identified were tote bags and their contents: journals, badges, craft materials and sensory tools (fidget toys).

The justification we provided was that the items were being used to support the practical workshops in schools and were part of the data collection. Participants used the journals during the workshop, responding to prompts and tasks through writing or drawing (giving us insights into their thoughts, feelings, experiences through creative processes); hence these were an important source of data contributing to our analysis. The bags contained pens, badges (used for communication preferences as well as names), arts materials for making activities and what are known as ‘fidget or stim toys’ (for sensory play/stimming). These ensured participants had access to the same set of resources, which is important for parity and inclusion. The stim toys were particularly valuable and popular with our neurodivergent participants, enabling the researchers and teachers to understand more about the role of stimming for this population (regulating emotion, facilitating focus, supporting processing). This was also important to creating a sense of group identity as the stim tools were something the participants used to interact with each other as well as individually. One participant described the resource as ‘my little bag of heaven’. The impact narrative for this project referred to a headteacher describing it as ‘changing lives’ due to the impact on individuals and the school as a whole.

There is pleasure and joy through the learning co-produced in these rich interdisciplinary research environments; the activities can produce tacit knowledge and felt understanding, the ‘moments of being’ Virginia Woolf describes, in which we perceive a new reality working in the arts/science interface. However, the query about the research rationale for these materials (and their relevance to the data) reminds me of Virginia Woolf’s fishing analogy in her essay ‘Professions for Women’ and her description of a young girl writing in contexts where a dominant authority stifles the work of an/other:

The image that comes to my mind when I think of this girl is the image of a fisherman lying sunk in dreams on the verge of a deep lake with a rod held out over the water. She was letting her imagination sweep unchecked round every rock and cranny of the world that lies submerged in the depths of our unconscious being. Now came the experience, the experience that I believe to be far commoner with women writers than with men. The line raced through the girl’s fingers. Her imagination had rushed away. It had sought the pools, the depths, the dark places where the largest fish slumber. And then there was a smash. There was an explosion. There was foam and confusion. The imagination had dashed itself against something hard. The girl was roused from her dream. She was indeed in a state of the most acute and difficult distress. To speak without figure she had thought of something, something about the body, about the passions which it was unfitting for her as a woman to say.’

Arts practices are embodied research approaches, requiring arts materials to ‘probe the dark places where the largest fish slumber’. I can only dream of a future heaven where this is no longer ‘unfitting’ for us as researchers to say, but instead is understood and valued as data.

What Is Data?

Last week, in the context of some work I’m doing for a client, I was trying to find something someone had written in answer to the question: what is data? I looked around online, and in my library of methods books, and I couldn’t find anything except some definitions.

The definitions included:

  • Factual information used as a basis for reasoning or calculation (Merriam-Webster)
  • Information, especially facts or numbers, collected to be used to help with making decisions (Cambridge English Dictionary)
  • Individual facts, statistics, or items of information, often numeric (Wikipedia)

Data is also, demonstrably, a word, and a character in Star Trek. So far, so inconclusive. Yet people talk and write about data all the time: in the media, in books and journals, in conversations and meetings. And they use it to refer to many other things than facts or numbers. Data may be anything from a piece of human tissue to the movement of the stars.

Euro-Western researchers conventionally speak and write of ‘collecting’ data. And indeed some data can be collected. If you want to research beach littering, you can go and collect all the litter from one or more beaches, and then use that litter as data for analysis. If you want to know what differences there may be in how print media describes people of different genders, you can collect relevant extracts from a bunch of articles and then use those extracts as data for analysis. So this is valid in some cases. However, if you plan to research lived experience by collecting data, you are effectively viewing people as repositories of data which can be transferred to researchers on request, and viewing researchers as people who possess no data themselves so need to take it from others. Clearly neither of these positions are accurate.

Some Euro-Western researchers speak and write of ‘constructing’ data. This refers to the generation of data as a creative act, such as through keeping a diary for a specified length of time, taking photographs during a walking interview, or making a collective collage in a focus group. Even conventional interview or focus group data can be viewed as being constructed by researcher and participant(s) together.

Autoethnographers and embodiment researchers privilege data from their own lived experience, though often they also use data collected from, or constructed with, others. But for these researchers, their own sensory experiences, thoughts, emotions, memories and desires are all potential data.

For Indigenous researchers, all of these and more can be used as data, which is often co-constructed with the researcher and all participants working together in a group. This is done in whatever way is appropriate for the researcher’s and participants’ culture. Māori research data is co-constructed through reflective self-aware seminars. In the Mmogo method from southern Africa, objects with symbolic and socially constructed meanings are co-constructed from familiar cultural items such as clay, grass stalks, cloth and colourful buttons, during the research process, to serve as data (Chilisa 2020: 223-4,243). Indigenous researchers in America, Canada and Australia use oral history, stories and artworks as data (Lambert 2014:29-35).

All of this tells us that data is not purely facts and numbers, as the definitions would have us believe. Conversely, we could conclude from the examples above that pretty much anything can be data. This does not mean anything can be data for any research project. You’re not likely to find a cure for disease by collecting bus timetables, or identify the best way to plan a new town by making inukshuk. But bus timetables could be very useful for research into public transport systems, and making inukshuk could be integral to Indigenous research into the knowledge and belief systems of Arctic peoples.

Data can be documents or tattoos, poems or maps, artefacts or photographs – the list is very, very long. And of course a research project may use different kinds of data, which could be collected, or constructed, or some of each. The question we need to ask ourselves, at the start of any research project, is: what kind(s) of data are most likely to help us answer our research question, within its unique context including any constraints of budget and/or timescale? In the end, for some projects, the answer will be facts, or numbers, or both. But if we assume this from the start, we close off all sorts of potentially interesting and useful options.

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The Power Of Naming

wordsWhen I first learned about research, as a student of Social Psychology at the London School of Economics in the early 1980s, the people we collected data from were called ‘subjects’. They were subject to our research, and subjects of our research; we were (told we were) the objective neutral researchers with the power to collect and analyse data. That power came from knowing how to do those things: special, arcane knowledge available only to insiders, i.e. those with enough educational capital.

By the time I got back into research, around the turn of the century, researchers had begun to acknowledge that positivism might not be the only game in town. The terminology had moved on and ‘subjects’ were becoming more widely known as ‘participants’. We felt good about this: instead of subjecting people to our whims, we would let them join in with our research (up to a point, mostly defined by us). How kind.

I’m beginning to think it’s time for another shift. I’m enjoying the way some researchers are being creative here, such as Alistair Roy with his ‘tour guides’. However, while that term works well for Roy who conducts walking interviews with marginalised young men in cities, it’s not universally applicable. So I’m wondering about… contributors?

I also think it might be time to rethink ‘data’. The word is drawn from the Latin meaning ‘something given’. Yet more often data is something researchers take and keep. The ability to classify things as ‘data’ has enabled serious abuses, some of which are still ongoing today. For example, in her magisterial book An Indigenous People’s History of the United States, Roxanne Dunbar-Ortiz demonstrates that Euro-Western researchers retain the human remains and burial offerings of millions of Indigenous people by classifying them as ‘data’. For Indigenous peoples, these remains and offerings are sacred, yet Euro-Western researchers continue to ignore their requests for the return of their sacred objects, using ‘science’ as the reason. On this basis it might make sense to reword ‘data’ as ‘loot’ or ‘swag’.

Another option would be to refer to people who provide information for research as ‘people’ and to the information they provide as ‘information’. I’m in favour of this because it has a levelling quality, especially if we researchers also refer to ourselves as ‘people’. It saves us from the irregular verb effect: I am a researcher, you are a participant, they are users of research.

All this is still researcher-led, though, so potentially paternalistic (or, in my case, perhaps maternalistic?!). A further option could be to let people who contribute to research decide how to define both their roles and what they offer to the process.

Some readers may regard all this as quibbling over semantics. However, given the strength of the relationship between language and thought, it seems to me important to consider these issues. Names have power: power to identify and classify. When we name individuals, roles, groups, artefacts, we are saying something about how we see the world. As always we need to use this power with care.

This blog, and the monthly #CRMethodsChat on Twitter, is funded by my beloved patrons. It takes me at least one working day per month to post here each week and run the Twitterchat. At the time of writing I’m receiving funding from Patrons of $23 per month. If you think a day of my time is worth more than $23 – you can help! Ongoing support would be fantastic but you can also make a one-time donation through the PayPal button on this blog if that works better for you. Support from Patrons and donors also enables me to keep this blog ad-free. If you are not able to support me financially, please consider reviewing any of my books you have read – even a single-line review on Amazon or Goodreads is a huge help – or sharing a link to my work on social media. Thank you!

What Offends People Makes Great Data

im-right-1458410__340Have you noticed how people seem to be getting offended about the strangest things? For example, there has been controversy this month over two songs that are regularly played in English-speaking countries at this time of year. The first is Baby It’s Cold Outside, a duet between two people (usually a man and a woman, though the lyrics are not gender-specific). It was written by Frank Loesser in 1944 to sing with his wife as a party trick. One character is persuading a slightly reluctant other to stay in the warm rather than go out into the winter weather. It’s flirtatious and funny, especially in my favourite version by Cerys Matthews and Tom Jones with an entertaining video which is worth watching right to the end. But some people say the lyrics promote date rape, and the song was banned by some radio stations earlier this month.

This is interesting as evidence of how our perceptions change. In 1944 no doubt date rape existed but it was not a widespread topic of conversation or media interest. In 2018, after #metoo, the world is a different place. So rather than looking like an innocent piece of comedy, to some people Baby It’s Cold Outside looks like a sinister instruction manual for would-be date rapists.

The other song that has been getting people hot under the collar is Fairytale Of New York, a more recent classic by The Pogues featuring Kirsty McColl. This is one of my two favourite seasonal songs. I love that it portrays people having an argument – so very common at this time of year – rather than the more usual saccharine sweetness. During the argument, two people hurl insults at each other, one uses the word ‘faggot’ and this is what has caused upset. (The other uses the word ‘slut’ but that doesn’t seem to be a problem… ho hum.) Shane McGowan, who co-wrote the song, made a dignified statement explaining that the song features two fictional characters who are not nice people so some of the things they say are not nice. He explains that storytelling requires unpleasant characters – which it does, or there is no drama.

One interesting thing about all this offence being taken is that more people hear about and listen to the songs. So people’s outrage, amplified by the media, has the opposite effect from that which they intend.

Perhaps words are easy to be offended by. It’s harder to be offended by the really offensive things going on around our planet such as famine and capitalism. We long for simplicity, for a world with problems we can solve. Yet banning a song containing the word ‘faggot’ is not going to fix global homophobia.

Research can be offensive, too. Of course unethical research is deeply offensive, but even careful, rigorous, ethical research can cause offence. John Bohannon, in his TED talk, said, “The great pleasure of science is the defeat of intuition.” I think that’s a wonderful sentence. Yet so many people hold fast to their intuition in the face of research evidence, outraged by the facts that challenge their beloved and long-held beliefs.

This, too, is interesting. I suspect this very human trait contributes to the barriers in translating research into policy and into practice. It certainly fuels many debates and slanging matches on social media. That gets exhausting sometimes… so I’ll be taking a break for the holiday season. See you in January!

This blog is funded by my beloved patrons. It takes me around one working day per month to post here each week. At the time of writing I’m receiving funding of $12 per month. If you think 4-5 of my blog posts is worth more than $12 – you can help! Ongoing support would be fantastic but you can also support for a single month if that works better for you. Support from Patrons also enables me to keep this blog ad-free. If you are not able to support me financially, please consider reviewing any of my books you have read – even a single-line review on Amazon or Goodreads is a huge help – or sharing a link to my work on social media. Thank you!

Aftercare in Social Research

aftercareWhen does a research project end? When a report has been written? When a budget has been spent? When the last discussion of a project has taken place? It’s not clear, is it?

Neither is it clear when a researcher’s responsibility ends. This is rarely spoken of in the context of social research, which is an unfortunate omission. A few Euro-Western researchers recognise the need for aftercare, but they are a tiny minority of individuals. There seems to be no collective or institutional support for aftercare. In the Indigenous paradigm, by contrast, aftercare is part of people’s existing commitment to community-based life and work. Euro-Western researchers could learn much from Indigenous researchers about aftercare: for participants, data, findings, and researchers ourselves.

The standard Euro-Western aftercare for participants is to tell them they can withdraw their data if they wish. However, it is rare for researchers to explain the limits to this, which can cause problems as it did for Roland Bannister from Charles Sturt University in Wagga Wagga, Australia. Bannister did research with an Australian army band, Kapooka, which could not be anonymised as it was unique. Band members consented to take part in Bannister’s research. He offered participants the opportunity to comment on drafts of his academic publications, but they weren’t interested. Yet when one of these was published in the Australian Defence Force Journal, which was read by band members, their peers, and superiors, participants became unhappy with how they were represented. Bannister had to undertake some fairly onerous aftercare in responding to their telephone calls and letters. Of course it was far too late for participants to withdraw their data, as this would have meant retracting several publications, which is in any case limited in its effectiveness. However, particularly in these days of ‘long tail’ online publications, we need to be aware that participants may want to review research outputs years, even decades, after the substantive work on the project is done. We have a responsibility to respond as ethically as we can although, as yet, there are no guidelines to follow.

Data also needs aftercare, particularly now that we’re beginning to understand the value of reusing data. Reuse increases the worth of participants’ contributions, and helps to reduce ‘research fatigue’. However, for data to be reusable, it needs to be adequately stored and easy to find. Data can be uploaded to a website, but it also needs to be carefully preserved to withstand technological changes. Also, it needs a ‘global persistent identifier’ such as a DOI (digital object identifier) or Handle. These can be obtained on application to organisations such as DataCite (DOIs) or The Dataverse Project (DOIs and Handles). As well as enabling reuse, a global persistent identifier also means you can put links to your data in other outputs, such as research reports, so that readers can see your data for themselves if they wish. This too is an ethical approach, being based in openness and transparency.

Then there are the findings we draw from our data. Aftercare here involves doing all we can to ensure that our findings are shared and used. Of course this may be beyond our power at times, such as when working for governments who require complete control of research they commission. In other contexts, it is unlikely that researchers can have much say in how our findings are used. But we should do all we can to ensure that they are used, whether to support future research or to inform practice or policy.

Researchers too need aftercare. In theory the aftermath of a research project is a warm and fuzzy place containing a pay cheque, favourably reviewed publications, and an enhanced CV. While this is no doubt some people’s experience, at the opposite end of the spectrum there are a number of documented cases of researchers developing post-traumatic stress disorder as a result of their research work. In between these two extremes, researchers may experience a wide range of minor or major difficulties that can leave them needing aftercare beyond the lifetime of the project. For that, at present, there is no provision.

Not much has yet been written on aftercare in research. If it interests you, there is a chapter on aftercare in my book on research ethics. I expect aftercare to be taken increasingly seriously by researchers and funders over the coming years.

An earlier version of this article was originally published in ‘Research Matters’, the quarterly newsletter for members of the UK and Ireland Social Research Association.

 

The Variety Of Indie Research Work

varietyOne of the things I love about being an independent researcher is the sheer variety of projects I work on and tasks I might do in a day. Yesterday, I was only in the office for the afternoon, yet I worked on at least seven different things. Here’s what I did.

First, I checked Twitter, and found a tweet with a link to a blog post I wrote about an event that is part of a project I’m working on with and for the forensic science community. This is a new departure for me, in that I haven’t worked with forensic scientists before, though the work itself is straightforward. I’m supporting a small group of people with research to identify the best way to create a repository for good quality student research data, and it’s surprisingly interesting. So I retweeted the tweet.

Second, I dealt with the morning’s emails. The arrival of a purchase order I’d been waiting for weeks to receive – hurrah! I formulated the invoice and sent it off to the client. Then some correspondence about the creative research methods summer school I’m facilitating at Keele in early July – just three weeks away now, so the planning is hotting up (and there are still some places left if you’d like to join us – it’ll be informative and fun). The most interesting email was a blog post from Naomi Barnes, an Australian education scholar who is considering what it means to be a white educator in the Australian school system. This chimes with the work I am doing on my next book, so I leave a comment and tweet the link.

While on Twitter, I got side-tracked by a tweet announcing #AuthorsForGrenfell, an initiative set up by authors for authors to donate items for auction to raise funds for the Red Cross London Fire Relief Fund to help survivors of the Grenfell Tower fire. I’d been wanting to help: my father is a Londoner, I have always had family in London, I lived in London myself from 1982-1997, and one member of my family is working in the tower right now to recover bodies. So it feels very close to home. But I’m not in a position to give lots of money, so I was delighted to find this option which I hope will enable me to raise more money than I could give myself. I have offered one copy of each of my books plus a Skype consultation with each one. My items aren’t yet up on the site, but I hope they will be soon because bidding is open already. If you’re one of my wealthy readers, please go over there and make a bid!

Then I spent some time researching aftercare for data. Yes, indeed there is such a thing. So far I’ve come up with two ways to take care of your data after your project is finished: secure storage and open publication. They are of course diametrically opposed, and which you choose depends on the nature of your data. Open publication is the ethical choice in most cases, enabling your data to be reused and cited, increasing your visibility as a researcher, and reducing the overall burden on potential research participants. In some cases, though, personal or commercial sensitivities will require secure storage of data. There may be other ways to take care of data after the end of a project, and I’ll be on the lookout for those as I work on my next book.

By now it was 6 pm so I did a last trawl of the emails, and found one from Sage Publishing with a link to a Dropbox folder containing 20 research methods case studies for me to review. They publish these cases online as part of their Methodspace website. I like this work: it’s flexible enough to fit around other commitments and, like other kinds of review, it tests my knowledge of research methods while also helping me to stay up to date. Best of all, unlike other kinds of review, Sage pay for my expertise. So I downloaded all the documents, checked and signed the contract, and emailed it back with a ‘thank you’. By then it was 6.30 pm and time to go home.

As the old saying goes, variety is the spice of life. I certainly like the flavour it gives to my work. Some days I work on a single project all day; those days are fun too. Yesterday I worked in my own office, today I’m out at meetings locally, tomorrow I’m off to London. It’s always ‘all change’ and I wouldn’t have it any other way.

Data

blimageLast week I received a #blimage challenge from @debsnet aka the édu flâneuse. When I came to the photo she had posted to inspire her challengees, it only took me a moment to link those overflowing hands with the data we researchers love to gather.

Data is a Latin plural word meaning ‘things that are given’, though it is used in English as plural or singular (e.g. ‘a piece of data’). In English it refers to information of various kinds: numbers, words, facts, opinions, pictures, tweets – the list is long. Social scientists can amuse themselves for hours by arguing about what constitutes data. There is a popular saying that ‘anecdote is not data’ although, when a qualitative researcher collects anecdotes from interview and focus group participants, data is exactly what they become.

Different types of researchers have different ideas about what constitutes data. To an anthropologist, an interview transcript may be only interesting for its textual content, while for a conversation analyst, the length of the pauses may be a fascinating aspect of that data. Some researchers treat focus group data just like interview data, while others see the interactions between people in the focus group as an enriching layer of extra data. For some people, data is collected; for others, it is constructed. I use ‘gathered’ when I want to encompass both perspectives.

Then there is ‘big data’: data generated by national governments, or by technology, which is so copious that it requires whole new methods of analysis and new words to describe its size like exabyte, zettabyte, or snakebyte (I might have made up one of those). Big data challenges the etymological suggestion that data is ‘given’ because big data is often a by-product of other activity, such as using social media or loyalty cards. This is an ethical minefield. For example, people may not realise that their data is of value to the companies running the facilities they use, and it can be difficult to track individuals down to seek consent for their data to be used in research.

You can do all sorts of things with data. For example, you can prepare data, code data, analyse data, synthesise data, visualise data, present data – and, if you’re like me, you can love data. In fact, I adore data! A new dataset to explore is so exciting because I never know what I might discover. I guess it’s the same feeling an archaeologist gets when they’re starting a dig, or an antiques dealer opening a box from a house clearance. There might be treasure in here! And even if there isn’t, even if there are only mundane things, I will still have seen something I hadn’t seen before, and maybe learned something new, or at least increased my experience.

You can also abuse and misuse data, by picking out the parts that support the argument you want to make, rather than preparing, coding, and analysing data as rigorously and honestly as possible. We are all susceptible to biases such as confirmation bias and hindsight bias, and there is only so much any one of us can do to counteract these. This is part of the reason for the scholarly peer review process, where others can scrutinise your work to check for bias. It is also why researchers encourage each other to track the links in our writing from research design, through data collection and analysis, to findings and conclusions, so that our processes and influences are clear to readers and they can make their own mind up about any biases they may perceive in our work.

It’s not only individual researchers, though, who abuse and misuse data. Research commissioners in every sector regularly bury data-based findings that don’t align with their political or organisational aims. And the media is notorious for putting spin on such findings. This has led to the establishment of independent fact-checking organisations such as Fact Check in the US and Full Fact in the UK.

It is easy to develop conspiracy theories about the ways in which governments, corporations, and the media use and misuse data. It is harder to do the tough research work necessary to counteract this, as far as we can, by producing firm findings, based on enough good-quality data, and presenting those findings in clear and understandable ways. To do that, we have to gather our data carefully, with a solid rationale for why we gathered it in the ways we did, so that we can be confident about the status and limitations of our data and about the findings we draw from its analysis. This is not easy – but it is possible, and it is our responsibility as researchers to do this work to the best of our abilities.

best spiderwebsNow, a #blimage challenge for Naomi Barnes: I look forward to seeing what she makes from this picture. And if anyone else would like to use it for inspiration: help yourself!