Let’s Play Big Data

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Turbulence - artwork based on algorithms and hand-drawn systems to create computational and natural system visualisations. Artist: Owen Schuh via DataIsNature

Turbulence – artwork based on algorithms and hand-drawn systems to create computational and natural system visualisations.
Artist: Owen Schuh via DataIsNature

The other day I overheard a student next to me on a flight say, “I can remember the words to almost every song I’ve ever heard more than once or twice – if only the legal cases I need to learn were set to music, I could remember them all.”

Optimistic, I know, but maybe not so far off.

Appeal to the brain’s pleasure center and learning becomes as easy as humming a well-known tune.

Along the same lines, researchers have been turning to crowdsourced data processing to work through big data conundrums. Offer a means of pleasurable participation for data entry, such as a game platform, and citizen scientist gamers will come.

Cancer Research UK worked together with game developers to create a smartphone game that would help them outsource a large backlog of genetic micro-array data garnered from thousands of breast cancer patients over the years. The result was Play to Cure: Genes in Space, which is basically a space shooter game in which the player finds the best path through an obstacle course, shooting asteroids and mapping successful escape routes.

A sample of genetic micro-array data. The analysis involves identifying the areas where the dots are at their most dense. Source: Gamasutra

A sample of genetic micro-array data. The analysis involves identifying the areas where the dots are at their most dense.
Source: Gamasutra

The possible paths, however, are actually maps of genetic micro-arrays, and the players game solutions are uploaded to the Cancer Research UK database for processing. After one month of use, gamers worked through data that it would have taken researchers six months to process without assistance.

The game version of the original data, with possible paths marked through the denser areas. Source: Gamasutra

The Genes in Space game version of the original data, with possible paths marked through the denser areas.
Source: Gamasutra

Another game, Geo-Wiki, deals with processing data on cropland cover and land use. From the Geo-Wiki site: “Volunteers review hotspot maps of global land cover disagreement and determine, based on what they actually see in Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a database, along with uploaded photos, to be used in the future for the creation of a new and improved global land cover map.”

The ‘game’ is a quick image/response competition. The platform can be expanded to include further agricultural and land-use data from users, which is then reflected in other projects that support better environmental monitoring.

The power of crowdsourcing is phenomenal, and I think we are just at the beginning of putting these tools to use outside of purely commercial marketing strategies. Having tried out both games, and having tried out the Geo-Wiki game, I think what’s still missing is that the games have to work on their own, as stand-alone games, for them to be truly addictive – and useful on a larger scale.EEHEoewC6vWEb-amrgU3OK2e5CXIY8I4aP6I52KHpuNcsBoUB8wD45If6sZhHuqhooIF=h900

 

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