‘Big Environmental Data’: 5 Key Insights from 5 Minutes with Dr. Paul Jepson
I armed Paul with only a 3-sentence email, 5-minute discussion, and 30 seconds to gather his thoughts before I hit ‘record’ on my iPhone. The 5 minutes that followed speak to his knack for creative thinking. Dr. Paul Jepson directs Oxford University’s MSc in Biodiversity, Conservation and Management program, which I graduated from in 2014. As students of Paul’s, many of us regularly met with him to have our neural messes untangled. But my most recent visit with him occurred following the MSc and during my MBA year at Oxford, in which I was required to submit a video of someone speaking on big data’s impact on his or her industry.
Big data has quickly become a buzzword and revolutionising movement most often associated with retail, finance, and health care. Data is gathered in never before experienced volume, velocity, and variety. Big data is now mainstream, having been praised and scrutinised in both popular and academic literature. Intriguing stories, such as the retailer Target’s ability to predict customer pregnancies based on purchasing habits, are often and continually attributed to big data analytics.
Paul was an easy choice for the assignment. For starters, I knew I’d leave his office with one or more insights that would keep me up at night. A meeting with Paul has an effect on the human mind similar to the effect that quarters have on a pinball machine. Secondly, Paul supervised my research dissertation on the topic of big data and environmental sustainability, and third, I was, of course, confident that Paul would nail the performance without much preparation. I procrastinated the hell out of this assignment, leaving no other choice, really.
So, in addition to the video itself, here are 5 key insights I took from Paul’s 5 minutes on big data as it relates to his field.
- Big data is newer in name but no less relevant to planetary management
…We’ve been thinking a lot about what I term, ‘Big Social Data’ — all of the data produced by transactions, by interacting with the social web, and so forth. But something I’m trying to get my head around a little bit more is what we might term, ‘Big Environmental Data’.
Paul hits on an important point right out of the gates. The big data movement has been slower to come into focus in the environmental field, yet its applicability and relevance are no less present than in other industries. Indeed, geographers have grappled with ‘big environmental data’ themes since the 1950s. Big data is however, relatively fresh to the environmental field in name, and it’s impact has already been massive. Organisations like the World Resources Institute (WRI), as Paul highlights, are demonstrating that big data solutions can be mobilised to yield positive environmental outcomes. Through the use of high-resolution satellite imagery, WRI has launched Global Forest Watch and Aqueduct, enabling organisations and the public to see where deforestation and water risks, respectively, occur worldwide.
2. Cheaper and smaller: ‘Big environmental data’ begins to align with the capitalist model
What’s really taking off now is a whole set of different sensors. So as sensors, I suppose, have gotten cheaper and smaller, we’re starting to see sensing filling that gap between … top level planetary satellite sensing and … a lot smaller, more local level sensing. And beginning to come on stream are vast amounts of new data.
Big data’s rapid uptake in retail makes sense. Target better understands customer purchasing behaviour through big data analytics, aligning with a profit-generating, capitalist model. Environmental efforts mostly lack profit-driven appeal however. Rather, they are often associated with risk mitigation efforts. Paul describes the changing characteristics of sensors that collect environmental data, calling attention to their reduced cost and size. GPS devices, for example, are now small enough to attach to birds, enabling an enhanced understanding of their migration patterns. Also, HP Earth Insights, in partnership with Conservation International, is an example of a localised sensing effort. Camera traps in remote regions around the world are constantly sending back data to reveal species abundance. As the ‘cheaper and smaller’ trend continues, we’re likely to see ‘big environmental data’ edge closer to the forefront of big data applications.
3. We haven’t even scratched the surface of ‘big environmental data’
…We’ve been managing the planet in a very data-poor world. The spatial and temporal resolution of that data is just transforming. Whereas previously we might have studied something, known about it 10 years ago and acted, now this has been compressed to having almost real time data on environmental change, and data which can integrate across scales and across sectors.
Paul goes on to emphasise that big data is enabling new ways of understanding how our planet functions, and these developments are helping us to transition from reactive to proactive planetary management. The cool-factor here is ever growing. We are witnessing new forms of environmental data collection through the use of new technologies. Acoustic or soundscape ecology is a rapidly progressing technology that’s allowing us to measure the health of ecosystems. Amazingly, we might in time understand how each sound in an ecosystem, including human-generated sound, connects to each species’ response and behaviour. Paul estimates that in 5 to 10 years we’ll see a complete transformation of ‘big environmental data’.
4. Equity and values are concerns with ‘big environmental data’
There are worries that the planet and our earth systems may start being managed by a group of technocrats and a group of some data scientists and information engineers…. And actually, where do people get a say in all of this? It’s just so complex that you really need almost an elite managing it. Perhaps it’s always been like that.
In all this excitement for the future of knowing our planet, we should pause to ask, ‘who manages all of this?’. People who lack data analytics skills will of course be reactive to the outputs from those who have the skills. Indeed, the leading conservationists of the future might require different skill-sets altogether. Furthermore, not everyone buys into big data. Some conservationists find that their values systems and big data solutions are misaligned, as preferences for hands-on work with nature are perceived to be at odds with distance-based technological solutions. Lastly, at the global level, the ability to collect data often relies upon the ability to afford information services. Data-rich countries therefore, have an advantage on ‘big environmental data’ efforts. Yes, big data critiques include issues of equity and values. So too should critiques of ‘big environmental data’.
5. We must be mindful of the paradox of disconnection through connection
As all of this data gets more and more sophisticated we can almost capture all of the different elements of an ecosystem…. Once we’re able to start putting all of this environmental big data into [virtual reality], it might be that we’re able to start walking in a … [virtual] natural world. So does this mean that people may lose the need to be connected physically with the natural world?
Paul discusses the virtualisation of nature. In other words, we are moving toward the ability to virtually experience the natural world. Through this virtual experience, will we lose the desire to physically place ourselves in real natural surroundings? Technology is allowing us to experience nature in many different forms, whether through the virtualisation Paul speaks of, observation through camera traps, live online safaris, or data visualisations. But there’s a line that’s crossed when big data is mobilised toward a technological experience of nature as an end-state, heightening the generational shift from outdoor to indoor activity. Rather, the true potential that surrounds ‘big environmental data’, aside from it’s ability to revolutionise planetary management, is in the enablement of new ways to create intrigue of ecosystem processes and change, resulting in the desire for real and meaningful human interactions with them.
In summary, many — if not all — of the costs and benefits associated with big data are transferable to ‘big environmental data’. I can only shake my head in amazement at the developments we’ve already witnessed, and the exciting bit is that ‘big environmental data’ has hardly been touched in practice or in popular literature. With people like Paul involved in the discussion, it’s only a matter of time before that changes, motioning us toward a transformation in the way we manage the planet, educate youth, and connect as individuals and societies with the natural world. The upside is however, matched by the downside. Big data truly has us facing big responsibilities and decisions.
All things considered, I am all for the mobilisation of the ‘big environmental data’. Frankly, we need it. A revolution has become an overdue necessity in all facets of humanity’s interactions with the natural world, culminating in human-driven alterations to earth systems, inhumane cruelty towards and ignorance of other species, and the widening gap between societies and nature. The old adage that, ‘If you continually do what you’ve always done, you’ll continually get what you’ve always gotten’, carries weight here. Let us explore and experiment then, bringing ‘big environmental data’ to the lexicon of big data in action.
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Top 5 Links
My working paper, ‘Big Data and Environmental Sustainability: A Conversation Starter’
WRI’s Global Forest Watch
Conservation International’s ‘TEAM’ Network
