Citizen Science
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A For the present account of citizen science, members of the public can collect, classify or interpret data across places and times that small research teams cannot cover. In public participation in research, the term sampling bias refers to a systematic difference between observations collected and the wider population of interest. The definition gives researchers a common starting point for discussing citizen science, but it does not identify a cause by itself. Two observations of citizen science can share the label sampling bias while differing in scale, timing or origin. B Knowledge of citizen science accumulated unevenly across large projects involving volunteers. A striking report could establish that a pattern existed, yet it could not show whether distributed observation operated elsewhere. Researchers examining citizen science therefore moved toward shared definitions and planned comparisons based on observer calibration rather than discarding the earlier record. C Researchers rely chiefly on observer calibration to investigate citizen science. Research on citizen science has found that volunteer records are compared with expert checks, repeated observations or known examples. They decide their comparison, exclusions and outcome measures for citizen science in advance. A result about citizen science is treated as stronger when it survives more than one source of evidence, not simply when one instrument measuring citizen science reports many decimal places. D The evidence about citizen science is informative but conditional. One point relevant to citizen science is that well-designed projects can produce useful broad-scale data, although participation and error are uneven. Researchers test distributed observation as an explanation. Evidence reviewed for citizen science shows that many contributors gather small pieces of information that become valuable when combined. Confidence in distributed observation rises when independent measures of citizen science agree and rival explanations fail, rather than when a single comparison happens to be statistically precise. E Practical programmes translate evidence about citizen science into action. The discussion of citizen science notes that projects provide clear protocols, training, feedback and meaningful ways for communities to shape questions. Their stated focus is research coverage. Teams working on citizen science compare later outcomes with conditions before implementation and record unintended effects. This evaluation of citizen science determines whether the original explanation involving distributed observation remains useful outside the research setting. F Interpretation of citizen science must stop short of a universal claim. For the present account of citizen science, easy-to-reach locations and highly engaged volunteers can dominate the dataset, and unpaid work raises questions about credit. Future work on citizen science is organised around co-designed protocols. For future research on citizen science, co-designed protocols will improve scientific usefulness and share decisions with participating communities. This use of co-designed protocols targets a specific uncertainty about citizen science rather than merely increasing the volume of data.