Birding 2.0: Citizen Science and Effective Monitoring in the Web 2.0 World * Ornithologie 2.0: la science citoyenne et les programmes de suivi à l’ère d’internet 2.0

Wiersma, Yolanda (2010) Birding 2.0: Citizen Science and Effective Monitoring in the Web 2.0 World * Ornithologie 2.0: la science citoyenne et les programmes de suivi à l’ère d’internet 2.0. Avian Conservation and Ecology , 5 (2). pp. 1-9. ISSN 1712-6568

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Abstract

The amateur birding community has a long and proud tradition of contributing to bird surveys and bird atlases. Coordinated activities such as Breeding Bird Atlases and the Christmas Bird Count are examples "of citizen" science projects. With the advent of technology, Web 2.0 sites such as eBird have been developed to facilitate online sharing of data and thus increase the potential for real-time monitoring. However, as recently articulated in an editorial in this journal and elsewhere, monitoring is best served when based on a priori hypotheses. Harnessing citizen scientists to collect data following a hypotheticodeductive approach carries challenges. Moreover, the use of citizen science in scientific and monitoring studies has raised issues of data accuracy and quality. These issues are compounded when data collection moves into the Web 2.0 world. An examination of the literature from social geography on the concept of "citizen" sensors and volunteered geographic information (VGI) yields thoughtful reflections on the challenges of data quality/data accuracy when applying information from citizen sensors to research and management questions. VGI has been harnessed in a number of contexts, including for environmental and ecological monitoring activities. Here, I argue that conceptualizing a monitoring project as an experiment following the scientific method can further contribute to the use of VGI. I show how principles of experimental design can be applied to monitoring projects to better control for data quality of VGI. This includes suggestions for how citizen sensors can be harnessed to address issues of experimental controls and how to design monitoring projects to increase randomization and replication of sampled data, hence increasing scientific reliability and statistical power.

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