The phenotype represents a critical interface between the genome and the envi-ronment in which organismslive and evolve. Phenotypic characters also are a rich source of biodiversity data for tree-building, and theyenable scientists to reconstruct the evolu-tionary history of organisms, including most fossil taxa, for whichgenetic data are unavail-able. Therefore, phenotypic data are necessary for building a comprehensive Tree ofLife. In contrast to recent advances in molecular sequencing, which has become faster and cheaper throughrecent technological advances, phenotypic data collection remains often prohibi-tively slow and expensive. Thenext-generation phenomics project is a collaborative, multidisciplinary effort to leverage advances in imageanalysis, crowdsourcing, and natural language processing to develop and implement novel approaches fordiscovering and scor-ing the phenome, the collection of phentotypic characters for a species. This research represents a new approach to data collection that has the potential to transform phylogenetics research and toenable rapid advances in constructing the Tree of Life. Our goal is to as-semble large phenomic datasets builtusing new methods and to provide the public and sci-entific community with tools for phenomic data assemblythat will enable rapid and auto-mated study of phenotypes across the Tree of Life
