Citizen Science Research at Syracuse

This recently started SOCS project examines strategies for dealing with the flood of digital data that confronts researchers. New techniques, tools and strategies for dealing with massive data sets, whether they consist of vast numbers of base-pair sequences or terabytes of data from all-sky astronomical surveys, present an opportunity to establish a 'fourth paradigm' of scientific discovery, but the task is not easy. In many areas of research, the relentless growth of data sets has led to the adoption of increasingly automated and unsupervised methods of classification.

The SOCS project investigates the capabilities and potential of social computational systems (SoCS) in the context of citizen science. Citizen science projects are a form of social-computational system. Whether it be volunteers playing a role in massive, distributed sensing networks exploring the migration of birds, or applying their unique human perceptual skills to searching the skies, human motivation and performance is fundamental to system performance. However, undertaking science through a social computational system brings unique challenges.

This completed project was a two-phase theory-based study of virtual organizations that enable massive virtual collaboration in scientific research. The virtual organizations studied have a core of scientists and project leaders coordinating the work of a larger number of volunteer contributors, a format called citizen science. The project was directed at advancing the understanding of what constitutes effective citizen science virtual organizations and under what conditions citizen science virtual organizations can enable and enhance scientific and education production and innovation.