Data quality is a primary concern for researchers employing a public participation in scientific research (PPSR) or ``citizen science'' approach. This mode of scientific collaboration relies on contributions from a large, often unknown population of volunteers with variable expertise. In a survey of PPSR projects, we found that most projects employ multiple mechanisms to ensure data quality and appropriate levels of validation. We created a framework of 18 mechanisms commonly employed by PPSR projects for ensuring data quality, based on direct experience of the authors and a review of the survey data, noting two categories of sources of error (protocols, participants) and three potential intervention points (before, during and after participation), which can be used to guide project design.
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