Abstract
Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge – creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described.
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Lukyanenko, R., Parsons, J., Wiersma, Y. (2011). Citizen Science 2.0: Data Management Principles to Harness the Power of the Crowd. In: Jain, H., Sinha, A.P., Vitharana, P. (eds) Service-Oriented Perspectives in Design Science Research. DESRIST 2011. Lecture Notes in Computer Science, vol 6629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20633-7_34
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DOI: https://doi.org/10.1007/978-3-642-20633-7_34
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