Low science, big data

A citizen science blog. Eye protection optional.

Introducing Citizen Science

#CitizenScience: Scientific research conducted not only by professional scientists but also by the lay public. Non-scientists can now become involved in open and democratic models of data collection and/or analysis.

Image: The Daily Green

First things first: what is ‘citizen science’ all about?
Well, it’s not an entirely straightforward since the term encapsulates a disparate range of initiatives. Ultimately, these projects generally share the ambition of remaking what it means to do science and who can be a scientist. This is done by involving the public in data collection and/or analysis. In many cases, data is viewed as a common good, a thing to be shared and worked on openly by anyone who wishes to collaborate. It’s worth noting that science has long been an amateur pursuit. For example, 17th century chemist Robert Boyle funded his science from the depths of his deep, deep pockets. Even Darwin relied on a network of amateur botanists and ornithologists, rural vicars and pigeon fanciers to collect data for him.

So what makes citizen science so relevant at the moment?

As you can see, scientific data has long been collected by amateurs, but now the prevailance of digital technologies is reducing barriers to access like never before. Today, new global movements seek to empower anyone to fund their own science and to crowd-source data from others. Social status and a mountain of cash are no longer prerequisites to enjoy the wonders of scientific discovery firsthand. Web 2.0 has delivered tools that aim to transform science by enabling the lay person to participate in and remake the scientific method. Enthusiasts are now able to collect, share and analyse data on scales that are able to surpass even the best professionals would be able to achieve alone.

Can you give some examples?

There’s lots out there and they are all a little bit different. Galaxy Zoo is a big one, with over a quarter of a million people becoming citizen scientists thus far. There’s so much data that it would have taken the pros many a lifetime to sift through it all. The project takes the images produced by NASA’s Hubble Space Telescope and gives them to people to classify. Sifting through hundreds of thousands of galaxies, volunteers are asked to identify shapes – a task that even advanced computers struggle with. This affords your average Joe and Josephine a rare opportunity to examine the darkest unseen depths of the universe and there are numerous instances of people discovering previously unknown object, all from the comfort of their bedrooms.

There are many more examples of similar crowd-sourced models of citizen science. Old Weather, Zooniverse and the SETI project are just three. These models take a large amount of data and ask citizens to sort it into a format that the professionals can analyse. But what interests me most is the projects in which citizens collect and analyse their own data from scratch. This is what I call ‘low science’.

Tell me more about this idea of ‘low science’…

There is no heirarchy – anyone can get involved in the whole scientific process. These models form from the bottom-up, out of nothing more than enthusiasm and interest. They are often messy and not particularly structured. They are highly experimental and that’s what makes them so fascinating – no-one knows if they will even be able to deliver results. The Air Quality Egg is just one very interesting and relatively large-scale example of this in action. Quantified Self is another interesting global community of low science experimenters and is all the most interesting because they are turning their own bodies in laboratories. I’ll spent a fair bit of time exploring these two projects as my journey into the world of citizen science continues…

 

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This entry was posted on March 28, 2012 by in Citizen Science and tagged , , , , , , , .

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