This project aimed to assess the information content in Citizen Science data for biosecurity surveillance by clarifying how the data collected through citizen science activities has the potential to be useful to biosecurity surveillance. Additionally, it looked at the inferential quality associated with citizen science data and the potential of fusing it with other information such as meteorological data and habitat suitability models in order to guide the development of practical surveillance systems based on this data.
An extensive literature study confirmed the novelty of this project. Despite a vast literature around Citizen Science, there is virtually none that combines Citizen Science with biosecurity surveillance. Given the specific definition of Citizen Science and the expectations of stakeholders, we identified that the topic of direct interest to Australia’s plant industries was Citizen Surveillance rather than Citizen Science. Citizen Surveillance can potentially incorporate a very broad range of data streams, and contribute to general surveillance in particular. To help frame the subsequent thinking and methods for extracting biosecurity surveillance information content, we developed a framework for classifying citizen science in terms of the degree of intention (why report and who to report to) and control (what, where and when) in the reporting, distinguishing between three main types: Crowdsourcing, unstructured citizen science and structured citizen science.