One of the projects he has been working on, in collaboration with Mark Hansen, Professor of Statistics at UCLA, is called Cascade which analyses the structures that underlie sharing activity via social networks on the web. He has also developed an app called Open Paths, where members of the public can upload tracking information from their iPhone and receive a visual representation of where they’ve been. Humans Invent spoke to Thorp about his work and how we can harness data for positive ends.
Would you call yourself a Data Artist?
I actually think of myself as a contemporary artist who happens to use data. I started to get into data maybe three years ago. I was working on a project which involved trying to build a simulated economy and I just found that without some information from the outside world it really wasn’t working very well. I started looking at outside sources and that got me into the whole process of data visualization and the whole community of data and it became clear to me that this change we were facing with big data and the sort of technologies related to data was going to be a transformative one and I thought it was a good thing for me to start exploring.
Well actually there are lots of other ways to represent data – you can turn it into sound and I even have some colleagues working with taste
Well actually there are lots of other ways to represent data – you can turn it into sound and I even have some colleagues working with taste. Any of our senses can be used to help us experience data a little bit better. There are some people who have that ability to look at a table of numbers and understand what’s going on but that is not very many of us.
What are the most interesting projects you’ve done?
I spent most of the last year and a half working on a project at the New York Times called Cascade, which is a tool to visualize how conversations happen within social networks, and that has been a really exciting project. We all know that content gets shared within social networks and that people are distributing things from one person to another but here we were able to see those systems for the first time. What I found interesting was that these systems are actually really complicated, there is lots of complexity with a lot of things happening underneath.
Can you tell me a bit about the Open Path project?
A group of us had read this article about how Apple had been using your location data on your iPhone without telling you and not surprisingly there was a big outcry over privacy and concerns that people would be able to access that data without it being password protected and so on. We had a different reaction, we just thought there is this huge source of data that would be useful to researchers so let’s try and get as much of it as we can before Apple closes the door on it.
We started this project and then it became clear to us there was more value to the project than just this mechanism to get this data from Apple. For me, the project has really become one about data ownership. We are really interested in giving people the experience of owning their own data. In most cases the person actually generating the data doesn’t see it or have access to it. We want to give people a chance to see the information that the phone provider is collecting about them.
Unfortunately, I think 80% of the dialogue around data is coming from the entrepreneurial community who are thinking about how they can make money from it
Unfortunately, I think 80% of the dialogue around data is coming from the entrepreneurial community who are thinking about how they can make money from it. However, there are a lot of interesting things happening with big data in cities where the data is being used to make people’s lives better in small ways. There is glacially slow progress happening in health care, which I think is an area with the richest possibilities for change through data. Epidemiology is a great example.
One of the things that we were thinking in the back of our heads with Open Paths was the way in which Epidemiologists model how a disease might spread in a population. In order to do that they need to know how people are travelling within that population and that can be quite a challenge. One of the big data sets available is this project called Where’s George? Basically, you can take any US dollar bill you have and enter the serial number and as more and more serial numbers are entered by people it starts to give you an idea of how people move through the country.