Georeferencing Animal Specimen Datasets

For biodiversity research, the field of study that is concerned with the biological diversity of our planet, it is of utmost importance that the location of an animal specimen find is known with high precision. Due to specimens often having been collected over the course of many years, their accompanying geographical data is often ambiguous or may be very imprecise. In this contribution, we detail an approach that utilizes reasoning and external sources to improve the geographical information of animal finds. We show that adding external domain knowledge improves the ability to georeference locations over traditional methods that focus solely on analyzing geographical information. Additionally, our system is able to output the confidence it has in its decisions through a confidence measure based on the difficulty of the instance and the steps undertaken