Mapping Life: Quality Assessment of Novice and Computer Automated vs. Expert Georeferences

Abstract: The majority of the world’s billions of biodiversity specimens are tucked away in museum cabinets  with only minimal, if any, digital records of the information they contain. Global efforts to digitize specimens are underway, yet the scale of the task is daunting. Fortunately, many activities associated with digitization do not require extensive training and could benefit from the involvement of citizen scientists. However, the quality of the data generated in this way is not well understood. With two experiments presented here, we examine the efficacy of citizen scientists in georeferencing specimen collection localities. In the absence of an online citizen science georeferencing platform and community, students served as a proxy for the larger citizen science population. At Tulane University and Florida State University, undergraduate students and experts used the GEOLocate platform to georeference fish and plant specimen localities, respectively. Our results provide a first approximation of what can be expected from citizen scientists with minimal georeferencing training as a benchmark for future innovations. After outliers were removed, the extent between student and expert georeferenced points was <1.0—ca. 40.0 km for both experiments, with an overall mean of 8.3 km and 4.4 km, respectively. Engaging students in the process improved results beyond GEOLocate’s algorithm alone. Calculation of a median point from replicate points improved results further, as did recognition of good georeferencers (e.g., creation of median points contributed by the best 50% of contributors). We provide recommendations for improving accuracy further. An important innovation would be creation of an online citizen science georeferencing platform.