Continental-scale citizen science programs rely upon dispersed networks of volunteers to gather information. Interactions between citizen scientists and principal investigators may be limited due to the large spatial scale and the number of participants involved. As such, overseeing data collection and ensuring the integrity of the data can be a major challenge confronting citizen science programs. A novel approach to reviewing data through an automated, geographically explicit set of data filters has been developed for the Cornell Lab of Ornithology’s Project FeederWatch. The project seeks to monitor the distribution and abundance of birds in winter across the
Results/Conclusions
Between November 2007 and March 2008 reviewers requested supporting documentation on 296 reports and received a response from 70% of participants. The review process led to the dismissal of 74 reports, the correction of 28 reports, and the confirmation of 104 reports including the documentation of two first state records. Unverified reports remain flagged and excluded from data analyses and web-based data output. This real-time validation system often allows participants to provide supporting documentation when the bird in question is still present at the site. The system also allows researchers to identify those volunteers that are in need of support and to focus educational efforts accordingly, ultimately improving data quality and integrity.
