Abstract
The increasing volume and variety of scientific data sets has produced a need for serious engagement with human computation. These citizen science efforts, which include disciplines as diverse as astronomy and zoology, are reviewed with a particular focus on Galaxy Zoo and the Zooniverse platform that grew from it. The key advantages of this approach—scalability, serendipity and the ability to inform machine learning—are demonstrated and the likely motivations of citizen scientists discussed. As datasets continue to grow in size, we argue that an increased focus on efficiency will be needed, but such an approach needs to carefully account for the likely effect on both motivation and on opportunities for learning.
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Lintott, C., Reed, J. (2013). Human Computation in Citizen Science. In: Michelucci, P. (eds) Handbook of Human Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8806-4_14
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DOI: https://doi.org/10.1007/978-1-4614-8806-4_14
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