Sam Hind: Your talk at CIM used this term ‘cold data’. Do you want to say a little on what that entails? Is it comparable, say, to ‘raw data’ or unprocessed data to some extent? Or are you working with something different?
Stephanie Posavec: I mention the term cold data because if you talk about data to a lay audience they see it as something that’s ‘cold’. The perception of people who might not really know what data is, or might not really come across it, who might see data as very cold, clinical and lacking personality. It has this neutrality to it. So the reason I use the term is because when I work with data – what I like to do as a designer – is explore using seemingly cold material (data), and data visualization, as a process to create a visual output and communicate a message that is often more subjective or emotional.
SH: The Dear Data project you did has a really rich ‘life’ to it, which doesn’t match up with this idea of, say, ‘cold data’. It seems like it’s the opposite of how people regard data…
SP: I think with Dear Data, what we were trying to do was to show people that anything can become data, it’s something that can be picked from any aspect of your life. So, what we really liked about the project was that we spent 52 weeks gathering data on a different topic each week, and these topics were really mundane, things like how often we checked a clock to see what time it was, or ‘laughing’. Just showing how data is everywhere, and that you can gather it from anywhere in your life. It’s not scary or intimidating, or cold.
SH: Going through some previous projects you’ve been involved in, such as Open Data Playground and Relationship Dance Steps, both of these struck me as great interactive pieces. To what extent do you think play is an important practice for understanding data? Do you consciously use that in your own work? Does it have a utility, say, when you’re organizing workshops with students, children, or whoever?
SP: When you play, you make mistakes, and you are imperfect. Play is making mistakes and being messy, and just doing what you want, not feeling like you have to adhere to any particular framework. I think that when it comes to data, and data visualization, because you don’t want to mislead, or to lie, and you don’t want to misrepresent something, there’s this level of honesty and rigor. I think honesty and rigor are both important, but not allowing people opportunities to make mistakes and learn can actually be restricting. Since I’ve worked in data visualization, I’ve found it quite an intimidating field because it makes the data ‘cold’ again. But just the act of trying to visualize something, or gather data that’s really difficult to gather is kind of a playful act. You’re accepting that it might not go anywhere, and it might not work. But, you’ll be closer a solution than you were when you started.
That’s why I like to work by hand when I gather data. It’s because I like working in a space where mistakes are kind of expected. You know you’ll never be able to do it quite perfectly. As a designer I like to say that I work in-between communication design and data visualization, so I’ll use a more rigorous process of data visualization and I still don’t want to ‘lie’ with my data – I’ll try to treat it faithfully, because I’m using that to communicate something that’s more emotive. So it’s this ‘fuzzy’ in-between space, where I’m not afraid to play with what a data visualization is. I like the challenge of trying to reconcile that.
SH: Also, like trying to represent data in more playful ways, the visuals themselves…
SP: OK, on the topic of play there, the thing I’m interested in is figuring out how we can move beyond traditional representations of data, and also because being a communications/graphics designer is an inherently playful occupation. There are people who are really experimenting with what is possible, with typography, or design and I think that level of play, that level of experimentation, is not necessarily translated to working with data. I think because there’s that other side of ‘science’.
So, designers are afraid of working with numbers. Even if you’re a designer who does work in that space you’ve got science shouting at you, but I really feel that graphic/communication designers should ask themselves why they aren’t being as playful with data as they are with designing a logo or a cover, or a lamp or a chair. I think what I’m really interested in is communicating data to a lay audience. People don’t really know what data is. I feel that, for certain audiences, it does need to be more appealing, more engaging. It does depend on your audience. The standard methods for data visualization are definitely the right approach if you need to design to make business decisions, or ‘scientific’ decisions. They’re perfect for that. But for someone who’s never really looked at air pollution data or you know, cared, maybe you need to communicate it in a different way.
It’s terrible to use the term, but maybe creative ways are ‘advertising’ the information within? I know that sounds really dodgy! It does all depend on your audience. As a designer my whole job is to deal with pretty wide audiences. I like the challenge of trying to communicate to as many people as possible. I like making something popular, but effective. It’s not easy! I’m basically advertising insights. I guess I’m an ‘insight advertiser’. That’s the bit that I like about doing weird data projects.
SH: I want to play on the deliberate ambiguity of the phrase ‘out of data’. In the one sense, it might refer to being ‘exhausted’ of data, or it might be that it’s something being ‘made out of’ data. Is there an interpretation of that phrase that you think is relevant or applicable to your own practice?
SP: It works in two ways for me. I like the term as in, yeah, ‘you’ve run out of data’ because I’m interested in data projects in which you are gathering data that’s very difficult to gather. Like in Dear Data ‘gathering your laughs’ (how often you laugh), you know it’s not going to be a perfect dataset, it’s difficult to gather that data. It’s this idea of trying to quantify or capture something that’s right on the edge. You don’t really know how to capture it, and I think I like that challenge. These are always the projects I’ve been interested in. These are the ones that computers often can’t do, because they’re kind of messy and there’s not really the technology. It’s something that requires a ‘human computer’. You know, when you’re trying to figure out how you’re going to get this data. I like working on projects that require human interaction and engagement. Can a computer (or is there an app?) that will gather all of my emotions, or every thought I have? I mean, no. Maybe one day, but how would it do it? I also see data as material that I use, as a designer. So, some people will use paper, pens or pencils. I use data as an ‘input’ to ‘output’ a visual I hope communicates something.
SH: Do you think your work has gained more popularity over the recent years, with the general public understanding that data (however defined) is even ‘a thing’ in the world? Has it made your job easier?
SP: I suppose, yes. More people are figuring out what data is. We’re all having to get used to it. It’s not exactly going anywhere. But where it doesn’t make my job easier, and I’m coming back here to the idea of ‘cold’ data; is that data is still always seen as a ‘negative’ thing. In many ways it is a negative thing. The NSA has tons of data! Think about all the data leaks. The Ashley Madison data leak, hackers ‘take’ data. It’s a threatening thing. That’s been the general narrative around data. Data, data privacy. A lot of designers and creators are making work that focuses on these themes, but I think that people will never really understand what that’s about if they don’t know what data is in the first place. Even with the Dear Data project, you just jump ahead if you just focus on, I mean, it’s really difficult to know what ‘big data’, ‘open data’ or data privacy is if you don’t even know what data is. It’s getting people to realize that anything can be data.
Also, my collaborator Giorgia Lupi and I did a book (Dear Data), and we did all these drawings in the book. Everyone collects data, it’s something that we all do. It’s just that we don’t realize that we’re doing it. We all have continual things we track, everyday (like our weight, for example), or how many people they’ve slept with or something! You know, this is all ‘day-to-data’. It’s using numbers as context, and using them to compare. Your number with other people’s numbers, all the time.
SH: Is that always good and healthy?
SP: No, no I don’t think it is! You know, like Klout scores and Twitter followers. Using data to compare yourself to others can potentially be unhealthy. But, one thing in the Dear Data project, because we had to gather data on ourselves for a week, we found it to be a positive thing. Like, that was ‘positive data’ because we had to be honest with the data we were collecting. It forces you to note down all these things in your life. You’re trying to get as much of an honest depiction of yourself as possible. Also, in that way, that personal data, for yourself, is useful.
SH: Did it make you more aware of the labour involved in recording some of this ‘personal ‘data?
SP: Yes, because then you realize what data should even be recorded. You know, I keep talking about laughter, but if you record every time you laugh it gets in the way of living your life, and laughing itself!
SH: A lot of the projects you’ve mentioned involved graphic designers and communication designers. You’ve presumably come across engineers working as Facebook’s artist-in-resident, what kind of opportunities are there when you work alongside people from different disciplines, on the same issue or project?
SP: Well yeah, I think it’s better to have more people working on a project from different backgrounds. I mean, I work for myself and having to collaborate on a project with someone else, like Giorgia Lupi, we thought we had a lot in common. Which is why we started the project, actually. But we actually think about data in really different ways, and we approach it differently. If I just kept going on my own, surrounding myself with people who thought my way I don’t think I would progress.
SH: Did it change how you constructed stuff out of data? Did it change the practices you engaged in?
SP: I think I’m inherently doing things the same way that I always do. But, it did compel me to try out other ways. To see how she (Giorgia) had explored the same things using the data, and how she visualized it. It would influence me to try it (Giorgia’s methods) out. Another thing that always surprises me is that you think that everyone knows how to visualize data, or do what you do with the same methods, but you realize they’ve got a completely different approach. That’s an eye-opener.
SH: I often find that interdisciplinary work is hampered by the lack of a shared vocabulary…
SP: Yes, in regards to collaboration, it depends on the dynamic of the space you’re in. I personally find, because the Dear Data project is so parallel, I like working with something who’s working differently to me because then we have our defined roles. But it’s when we’re ‘equal’ this way of working has been a real challenge. It’s actually more stressful. Like, if I work with a developer we might have an overlap but no one is stepping on each other’s toes.
SH: Did you compare methods in Dear Data?
SP: We would both have the same theme, but we gathered data in our own way. So, I generally used this app called Reporter (http://www.reporter-app.com/). You can set-up all these questions (in the app) and downloaded the data at the end. It’s created by Nicholas Feltron who’s done a lot of annual reports gathering data on his life, who’s a friend and also probably a really big influence. So, the way that I would gather data by setting-up the questions that I wanted answering, and going out and collecting it. Georgia did it differently. She just wrote every single thing down, and then timestamped it. She just had tons, and tons of notes. Then she categorized it. I didn’t realize that we were doing it quite so differently. That’s quite a different way of doing it, you know? She just ‘dumped’ everything, in a sense. But because she was doing it that way, her output is much more detailed than mine. She gathered ‘everything’ and put it into the boxes later. Whereas I set-up the boxes in the questions, in the beginning, and I preferred it that way.
Stefanie Posavec’s co-authored book with Giorgia Lupi, ‘Dear Data’, is out now.