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Tuning the Citizen Science “Instrument” for Gathering Data While Documenting Data Quality
Heejun Kim is a PhD student in the School of Information and Library Science (SILS) at the University of North Carolina at Chapel Hill. He has a MS degree in Geographic Information Science (GIS) from the University of Illinois at Urbana-Champaign. His research interests are in information extraction from user-generated content, credibility assessment in participatory environment, geographic information and disaster management. In his spare time, Heejun likes swimming, cooking, and playing with his two sons.
Citizen science is a novel “instrument” that can gather data unavailable to scientists using traditional methods. Recent advances in internet technologies and mobile computing are accelerating the possibilities to engage the public in participating in scientific research. Projects such as eBird and CoCoRaHS are providing data that is proving exceptionally to scientists. Nevertheless both the scientific community and the public remain skeptical about the quality of citizen science data because citizens by definition are not “certified” scientists. To overcome this hurdle citizen science projects use variety of approaches to improve and document data quality. The candidate will mine the web and use a literature review process (perhaps combined with web surveys and/or personal interviews) to document citizen participation, data collection procedures, and analysis tasks undertaken by citizens. Building on the efforts of Wiggins et al 2011(Mechanisms for Data Quality and Validation in Citizen Science), the candidate will document methods to improve and document data quality. One goal will be to define data models and data quality models that can guide citizen science projects in the future. A second goal will be to better understand and define the essential tension between improving the data quality (having citizens work like scientists) and keeping the citizens engaged in the project.