Using Big Data to ask better Questions
Finding great answers always starts with great questions – however in today’s world we are often overwhelmed by enormous amounts of data.
If only we knew the “right questions” we would be so much closer to a better understanding of the world around us and our interconnectedness.
Eric Berlow shows us that “complex doesn’t always equal complicated” and “simplicity often lies on the other side of complexity”
What would happen if we could more easily sort through some of the data with good visualisation tools to better spot the underlying patterns and linkages.
What matters the most will show up in a visual form that our brains can more easily deal with. Here is what that might look like.
I have slightly enhanced a screenshot from the video to show more of the nodes but the real power of this is the when you watch the network on the video and can flip it around to isolate and determine which data is the most useful.
Eric goes on in this data visualisation to show us that most of this data can be sorted into actionable and non actionable and and so on. What he shows us is that simple answers may indeed emerge.
There are other ways of understanding the data and in this scenario much of the content came from a newspaper infographic which was overwhelmingly complicated but not really that complex if we have visualisation tools.
Eric Berlow is an ecologist and network scientist who specializes in not specializing. He helped found, and directs, the University of California’s first environmental research center in Yosemite National Park. More bio on Eric over here Eric is on twitter @ericberlow
This gives rise to a whole new set of questions and by using these better questions and being able to more easily understand and sort through the complexity we find much more clarity and simplicity on the other side.
Jer Thorp creates beautiful data visualizations to put abstract data into a human context. At TEDxVancouver, he shared his moving projects, from graphing an entire year’s news cycle, to mapping the way people share articles across the internet. He is thinking about data in a human context.
“Jer comes from a background in genetics, his digital art practice explores the many-folded boundaries between science and art and shows us again how a more visual view of the data helps us to decode and simplify and understand meaning on a more human scale.”