Adventure on the Okavango: The Data Artist
(Part 2 of 2)
Data artist and National Geographic Emerging Explorer Jer Thorp gets up close—sometimes terrifyingly close—to wild animals in the Okavango Delta and records his experiences as interactive visualizations, allowing anyone with an Internet connection to take a real-time journey deep into the Okavango. Click here to see Part 1 of this series
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Transcript
When we put together the proposal for this talk, I suspected that many people would be wondering about this pair, pairing of data and the wilderness, because I think the way we think about those two words, they're quite far apart. We don't think of those things being paired together but... I hope that we'll find out over the next few minutes that that they actually do go very well together indeed.
The word data, we hear this word every day now. And it's something that's become really ubiquitous in our lives. The definition of data is fairly simple. Data are measurements of something. But it... the word itself has become something much more than that. And what I want to talk about today is I want to talk about the idea of data paired with this concept of distance. I estimated here and I think I estimated generously, but standing in front of you in this crowd today the hippo in question was somewhere about the middle of the crowd. And, some hippo data, in case you don't know a male hippo, they're the, mostly the angry ones. They weigh about three and a half tons. They're five feet tall and 13 feet long. This is an angry minivan.
It may surprise you from looking at me but I was not a rugged explorer type when I was a child. And I spent most of that time exploring through the computer. And since then I've used the computer and tools that have been created to make art with the computer. And, I started to use data. The simple examples are these stylized charts and graphs. This is a graph showing the frequency of the words communism at the bottom and terrorism at the top in the New York Times between 1980 and 2010. Now, all of this hinges on the fact that data is a deeply human artifact. There would be no data without humans. We create it. Our normal understanding of this is something quite different. And so when Steve approached me to work on this project, one of the primarily exci-- things that I was very much excited about here was how can we remind people of the humans that are on this expedition and how can we track them at the same time that we're tracking the wildlife which is the primary focus of the science.
And while I was at the New York Times, I was at the Times for two and a half years as their data artist in residence, I produced along with a couple of collaborators a project called Open Paths. It allows you to do exactly what every other app in your pocket does but with one big difference. And that is that you can turn around and look at the data first. And second, nobody owns that data except for you. So, we built this project. I installed Open Paths on my phone and kind of forgot about it. And about a month later, I came back to the website where you can view your own data and see where you've been. And I realized that this data that I was tracking represents something that's fundamentally important to me which is my own personal narrative. The actual story of my life. And... and with the website you can make a couple of different comparisons with it, it's a really straight forward visualization. But thinking about what this data is started to bring me towards what I think is the most important question in my practice which is, how can I build a personal relationship between me and my data? And my goal and the goal with this project is to remind us of that and also to bring that gulf between data and humans closer together.
Now, in this closeness that to... the wilderness that Steve described, as much as I have tried to prepare myself for was impossible to prepare for the reality. So, this is us, we are strapped in, in these portage harnesses and we are pulling these mokoro some of which weigh well over 500 pounds through sticky mud. The reeds are razor sharp, our legs are covered in blood and leeches. It's 110 degrees and, and... and we really have become one with this environment. But at the same time our goal, Shah's goal, my goal was to collect data at every moment that we can. So, this is Shah in his field station, an upturned Tupperware bin and he is recording water quality measurements that we then upload to our website. And we would also in the evening, we would try to get as much of the record of the day as we could sorted out and depending on our bandwidth analysis, get that up into the website.
And what we were trying to do, I think, for the first time was to build a truly live data expedition. Now these little colorful dots that you've been seeing on the side of the screen are actually data points that we collected during the expedition. Each one of them representing a sighting of a species. So, as we are traveling down the river, something amazing was happening and that was with every data point that we were collecting was uploaded via satellite to the website generally within five to ten minutes and it was available to the public. So the public could not only see those data points appearing on the map they could use them in their research, they could use them in their classrooms and our goal here was to try to bring the wilderness to the real world.
So this is how it'd work. This is an African Skimmer, actually quite a rare bird. It has an adaptation in it's beak which allows it to skim the surface and catch insects from the water. So, we may stumble upon three African Skimmers and Steve would say, “Three Skimmers.” Giles, who is sitting in front of him in the boat, would use a custom made Android app that we built for the expedition to report this sighting of three Skimmers. That would send the data to a little Raspberry Pi. A Raspberry Pi is a $30 computer that we built inside of a little pelican case that sat in the back of the boat. And that little antenna that you see is talking up to the satellite. So the data would immediately be sent up to the satellite to the website, where it would appear for the public. It's something that we're really proud of because it allows people at any point during the expedition to come in and really feel what this experience is like to understand the time-based nature of it, to understand the difference between these sparse Papyrus canals that we were travelling through the first days to the central delta where the wildlife concentrations are bigger and denser than almost any other place on Earth.
This is the fundamental idea of the project. Can we turn the idea on its head that the reason why scientists go into-- go into the field, the reason why they go on expeditions is so that they can gather data that no other scientist has. And that's the fundamental reason why expeditions are appealing to scientists. Because they are going to be able to get access to something that nobody else has seen. So, with our project, we flipped that. Right away, as soon as we're making our measurements in the field this data is available not only to our team but to any other research team who may not have the budget to get into the Okavango and to anybody else who is interested in this wilderness area.
So, what you're seeing here is every species sighting that we saw along the actual track of the expedition. So we can look for pattern in species we can see how this is changing over time. And the idea is to build this tool into something that anybody can use. Our number one focus is to make all this open. We are also building these sensor platforms. These are a couple of the sensor platforms before they were deployed. This is one of the test sensor platforms after it's been deployed. And if I had my cell phone with me, I don't right now, I can actually go and look at the API right now and I can get an accurate pH and temperature measurement from this body of water in the Okavango from right here on stage and anybody can do that. And next year we are hoping to deploy a network of up to fifty of these sensors throughout the delta so anybody... scientists, the curious, can get a look at this ecosystem.
One of our challenges is how do we get more people involved in this project. And one of the things that we've been working on with Shah is to take the underlying infrastructure of the Into The Okavango project and to release it as a fundamentally open source project that any other expeditionary scientist can use. So, we're starting to work on this right now. The Open Data Field Kit will be available to anybody to be able to do the same things that we're doing in the delta other wilderness areas, in other urban areas, so that data could be something that automatically gets shared with the public. And our intent here is to produce a data legacy. We want to produce a data legacy for everybody. For teachers, for students, for artists, for designers for researchers, for anybody who wants to use this information.
Because as important as our travels into the delta are, they are going to have limited impact if we can't get this out to everybody. And it's simple to get involved. You can follow us on, on... on our Twitter feed which is @IntoTheOkavango. You can follow the website. And together we can try to bring these three seemingly disparate things together. Now... I know I didn't finish.
We're all wearing these heart-rate sensors on our arms which are recording our biometrics and-- So, I actually do have an exact record of what it's like to be charged by a hippo. And I'm going to let you listen to it. So... - I'm on the right and you are going to hear the actual in-time heartbeat. I'm going to start it and it's going to pause for a second and then it's going to play up to when the hippo charges. I'm not even going to tell you what time it is because it's obvious. Now, I want to point something out because Steve is sitting right here. He said that he was concerned about me but look at his heart-rate. He's cool as a cucumber over there in the front boat. And I hope this leaves us with an example and a reminder of the things that we can do through this project and through changing our understanding of data to bring us from a place, where this information is something made by machines, this information that is something that is cold and numerical, to being something that can be shared, can be talked about, can be performed, can be used to tell stories, can be used to teach, can be used to inspire.
As Steve said our mission in the Okavango is critical. We have two years to cha-- to make change, to make sure that this pristine environment remains pristine and I can really think of no more important goal. So, please join us as we enter the Okavango again and follow along with the experience, both through the data and through your ability to... to connect to us as explorers and we hope that we'll have some more stories to tell for you next year. Thank you.