Title: Managing the Public to Manage Data: Citizen Science and Astronomy,
Abstract: Citizen science projects recruit members of the public as volunteers to
process and produce datasets. These datasets must win the trust of the
scientific community. The task of securing credibility involves, in part,
applying standard scientific procedures to clean these datasets. However,
effective management of volunteer behavior also makes a significant
contribution to enhancing data quality. Through a case study of Galaxy Zoo, a
citizen science project set up to generate datasets based on volunteer
classifications of galaxy morphologies, this paper explores how those involved
in running the project manage volunteers. The paper focuses on how methods for
crediting volunteer contributions motivate volunteers to provide higher quality
contributions and to behave in a way that better corresponds to statistical
assumptions made when combining volunteer contributions into datasets. These
methods have made a significant contribution to the success of the project in
securing trust in these datasets, which have been well used by other
scientists. Implications for practice are then presented for citizen science
projects, providing a list of considerations to guide choices regarding how to
credit volunteer contributions to improve the quality and trustworthiness of
citizen science-produced datasets.