Calling all Citizen Scientists: using Bayesian Statistics to advance public input into scientific analysis


Many scientific projects are benefitting strongly from the contribution of information by community members. For example, citizen scientists might classify arrays of ecological images or express risks about medical or social outcomes under hypothetical scenarios. However, these data can pose challenges for the scientist and analyst. Three such challenges are how to elicit the required information when this is in the form of expressed opinions, how to combine these opinions, and how to evaluate the credibility of crowd-sourced data.

In this presentation, I will describe the efforts of members of our research team to address these challenges, and set this work in the context of a number of case studies that motivate the research. In particular, I will focus on the use of Bayesian models to frame the problem, incorporate the various sources of information and express the desired probabilistic outcomes. These approaches include Bayesian Networks, spatial measurement-error and item-response models, and meta-analysis.

This research has been undertaken in collaboration with a range of colleagues who will be acknowledged in the presentation.

About the speaker

Kerrie MengersenKerrie Mengersen is a Distinguished Professor in Statistics at the Queensland University of Technology in Brisbane, Australia. She is the Deputy Director of the Australian Research Council Centre of Excellence in Mathematical Frontiers and the Director of the QUT Centre for Data Science.

Distinguished Professor Mengersen is acknowledged to be one of the leading researchers in her discipline.

Her research interests are in mathematical statistics and its application to substantive challenges in health, environment and industry, with particular focus on Bayesian methods.

Professor Mengersen is also an elected Fellow of the Australian Academy of Science and the Australian Academy of Social Sciences, and a member of the Statistical Society of Australia and the IMS, ASA, RSS, ISBA and ISI.