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HCIL Brown Bag Lunch: Citizen Science at Scale: Human Computation for Science, Education, and Sustainability
HCIL (2105 Hornbake Building, South Wing)
Thursday, October 23, 2014, 12:30-1:30 pm Calendar
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Abstract

Citizen science is gaining recognition as an innovative mode of scientific collaboration that engages the public in real-world research. Increased coordination and communication capacities attributed to technological advances have lead to dramatic growth in the scale, scope, and impact of public participation in science, while also enabling novel research that would not otherwise be feasible. In addition, citizen science is full interesting challenges for HCI, with notable needs and opportunities for innovation in such areas as sensors, DIY technologies, mobile applications, painless data entry, usability for "K through gray", STEM learning technologies, and data visualization and exploration tools. 

This talk will introduce two projects focused on supporting large-scale participation in citizen science from a data-centric perspective. In the eBird "human-computer learning network", 40% annual growth in data submissions to one of the world's largest biodiversity data sets creates a challenge for data validation by a limited pool of experts. Our team has applied AI and machine learning to refine the system's dynamically-generated data entry interfaces, reducing the incidence of "false positives" for outlier records that require expert review. In addition, we have developed a method to estimate contributors' expertise based entirely on their data submissions, and examining time series of these expertise estimates also suggests a learning effect through ongoing participation. The expertise estimates are currently being incorporated into spatio-temporal models of bird migration to reduce noise introduced by the natural variability in diverse human observers. 

The second project, recently funded by the NSF CyberSEES program, will develop proof-of-concept infrastructure to deliver biodiversity data from science classrooms across the US to researchers that need data for ongoing research. Through partnerships with several sustainability science projects and the Smithsonian BioCubes program, student-generated data will be integrated with data collected by professional scientists to support ecological studies monitoring the spread and impact of invasive species, the biogeographic and evolutionary effects of climate change, and community changes in species-rich but vulnerable coastal marine ecosystems. The UMD team will investigate the factors that enable and prevent participation by both data producers (learners) and data consumers (scientists), in order to inform the design and development of current and future cyberinfrastructure.

This talk is organized by Daniel Pauw