Next Generation Taxonomy, Can high throughput DNA barcoding, machine learning and open data enhance species discovery?

What? Our planet is populated by millions of insect species which are not taxonomically studied because of their megadiversity and slow pace of this field of science. Due to anthropogenic habitat destruction many of such species are going extinct and at a fast rate. For example, we risk that most insect species will disappear before we name and taxonomically describe them. We can speed up the taxonomic process by using modern technology. For example it may be possible for robots to sort thousands upon thousands of insects. Many will be recognized purely by computer vision and the few that cannot will go into DNA barcoding protocols. Images, DNA barcodes and AI will enable fast and precise information of the known and unknown insects, enabling rapid yet resilient taxonomic work. Why? If we can successfully set new standards for the generation and synthesis of biodiversity data, we could revolutionize the way natural history museums, researchers, and NGOs work by unlocking the potential of the 'raw' data within museum collections. This will be applicable not only for taxonomic work, but also for species conservation, biological legislation and ecological research where the need of a biological species name is an impediment for the swift documentation of biodiversity and thus the conservation hereof. How? Together with Rudolf Meier at the Center for Integrative Biodiversity Discovery at the Museum für Naturkunde in Berlin we will further expand upon his work of the last 20 years in the field of next generation of insect biodiversity research. We will further develop on DiversityScanner a robot, that sorts and identifies insects based on computer vision, so that it can start describing the features of each insect, a taxonomic description (link: https://youtu.be/ElJ5VSHa4OI). Another major breakthrough is the rapid DNA barcode generation archived through next generation sequencing. Coupling these will allow for the automated description of the variation within each species clusters revealed through DNA barcoding.