For Love Data Week (12th-16th February 2018) we are featuring data-related people. Today we talk to David Marshall, FutureLib Project Coordinator, University Library
Telling Stories with Data
Let’s start with an easy one. What kind of data do you work with and what do you do with it?
I deal primarily with qualitative data collected through working with people, gathered in a number of different ways. Research methods tend to include things such as in-depth interviews, observation and shadowing, diary studies, as well as various remote data capture mechanisms. I am usually looking for a mix of attitudinal and behavioural data; comparing what people say with what they actually do. I use the insights and findings arrived at through the analysis of this data to make recommendations for service design and delivery on behalf of Cambridge University libraries.
Tell us how you think you can use data to make a difference in your field.
I am an advocate for the importance of using research and research data to understand the wider lives of people who use a product or service. This has long been an established principle in service design and delivery in the commercial sector, and libraries in UK Higher Education are learning to adopt this in order to tailor their services to the approaches, goals, needs and behaviours of their users. The data I work with often highlights aspects of the study and research lives of Cambridge students and academic staff which it would be difficult to fully uncover and explore through more ‘traditional’, quantitative methods, such as usage statistics and surveys. This in-depth, qualitative study of people provides valuable insights which can be used to inform the development of services and working practices that affect those people.
My ‘field’ is working within and for University of Cambridge library services; slightly oddly I am often conducting research, with researchers as the subjects of that research, with the aim of developing services that support research!
How do you talk about your data to someone outside of academia?
I’m going to turn this one on its head as, although I work within academia, I’m not involved in what would typically be described as academic research. I tend to refer to what I do as design research, i.e. with the end goal of using the data gathered and insights arrived at to inform service design and delivery. I often talk of ‘stealing’ methods from academic disciplines and areas such as anthropology and ethnography, and from the commercial design world. This can involve immersive research techniques such as ethnographic observation, or quick, easily-deployed techniques such as card sorting exercises and ad-hoc interviews. In terms of the data itself, I often talk of patterns emerging and insights developing. Immersing myself in the data over the course of its collection, through activities and tasks such as transcription, and again through the analysis process helps things to ‘take root’ and for these patterns and insights to become more clear.
Connected Conversations
What data-related challenges do you have to deal with in your research environment?
Collecting the data in the first place is one of the biggest challenges for me. To do my work I need data from real people, leading real, busy lives. Finding and connecting with the people I need to work with is a constant challenge. Happily, the need to go to people where they are and work around their schedules in fact leads to better data; I would much rather talk to people about their studies, research, or other aspects of their lives when they are in the middle of doing those things! Another challenge is finding the right tool for the job; over the years I have been lucky enough to work with and learn from people who have extensive experience in a wide variety of research techniques, but it can still be tricky to match the appropriate method/s to a specific question or area of study.
To add a more data-related challenge to the list of data-related challenges…: I deal with a lot of personal data, not just names and demographic information but a large amount of qualitative data gathered from individuals about their lives; their goals, motivations, points of frustration, and so on. This leads to challenges in terms of how data is collected, stored and used, even how it is considered during the analysis process.
How do you think these challenges might be overcome?
For my first points: the old Carnegie Hall adage… practice, practice, practice! Relationship building and communication is a huge part of what I do day-to-day; each time I need to find research participants it becomes a little easier due to the continuous work done in this regard over the years I have been working in my role.
For the latter: I think appropriate awareness is part of the battle. Working with research data, particularly that gained from working with people, demands high levels of awareness and an emphasis on reflection, and so it should! It is important to see qualitative data in context, for many reasons, and to be constantly aware of the ethical implications of its analysis and use.
If you were in charge what data-related rule would you introduce?
That every person I’m interested in finding out more about needs to supply me with it tout suite, please and thank you. No, that might be going too far…!
Without being specific, anything which increases the transparency of what will happen to data after it has been gathered is a good thing. I rarely struggle to get people to consent to participating in research once I have found and approached them, and am as transparent as I can be about why I need their data, what I’m planning to do with it, and where it will end up. Maybe I’m blessed by the context within which I work, and might be slightly naïve, but I can’t help but think that on any scale and in any circumstance this emphasis on transparency might be quite a useful thing.
We are Data
Tell us about your happiest data moment.
Around two years ago we (Futurelib) finished the data gathering phase of a project, Protolib, looking at the design of physical study spaces. We had prototyped different study spaces based on the findings of a collaborative design process conducted with Cambridge students and researchers. We conducted hours (as in 300+ hours…) of observation in these prototype spaces, and gathered data in various other ways, such as interviews with people leaving the spaces, feedback walls, comment cards and questionnaires. The first thing we did as researchers after this was to brainstorm the insights we had arrived at from this work. To see themes and ideas emerging so quickly, and to see them backed up and added to by the research data, was amazingly fulfilling. This is what ‘sold’ me on the value of ethnographic techniques; we had immersed ourselves so fully in the environments under study that we understood them to an extent which I would not have previously thought possible.
What advice do you have for someone who is just embarking on a career in your field?
Want to learn. Get interested in people; who they are, how they think and what they do. I don’t much like the idea of the cold, disinterested researcher. Whilst being aware of your own potential biases, and biases based on what you learn and uncover, care about the people you are working with and try to emphasise as far as is possible with what is important to them. If you don’t like talking to people and finding out about the way they work, this is possibly not quite the right job for you. Of course, there are areas of research in which disinterestedness is probably a very valuable characteristic, I just don’t think this applies to what I do.
What do you think the future of research data looks like?
Speaking about the context within which I work day-to-day, I think the future looks bright! Libraries and HE institutions are becoming increasingly interested in finding out more about the people their services support. In my area of work, usage statistics, quantitative survey mechanisms and other similar methods will always provide the broad strokes, and this is great. It is, however, absolutely not where gathering data should stop. I cannot over-emphasise the value of qualitative approaches and qualitative data in providing actionable evidence for service design.
In terms of the future of research data more generally, I don’t feel too qualified to comment… I would tentatively assume and hope that data will become more accessible, less owned, more malleable, and through this invite more discussion, criticism and conversation.
There is A LOT of data out there about all sorts of things and it is being collected all the time. Does anything frighten you about data?
From a personal standpoint, potentially losing focus. It is almost the modus operandi of what I do to collect as much data as possible about the lives of people studying and working at the University of Cambridge, so I do feel that I collect ‘A LOT’. I sometimes wonder about the nature of the data I gather, as I’m keen to emphasise with participants that I’m interested in all aspects of the ways in which they work, and more widely, the ways in which they live. This does, on occasion, lead to people sharing quite personal aspects of their lives. There are obvious concerns around how this data is handled and used, but, as mentioned previously, I feel that an appropriate level of awareness and diligence in this regard is a good starting point for working with this kind of data in a sensible, conscientious way.
Published 16 February 2018
Written by David Marshall
@futurelib
Let’s start with an easy one. What kind of data do you work with and what do you do with it?
Let’s start with an easy one. What kind of data do you work with and what do you do with it?