GOTIT: A laboratory application software for optimizing multi‐criteria species‐based research

Abstract

Abstract Storing, managing and sharing the ever‐increasing amount of species occurrence data and biological vouchers is a cornerstone of biodiversity science. The convergence of morphology‐ and DNA‐based methods for species delimitation has accentuated the need for optimizing laboratory workflow by generating new analytical processes, diversifying taxonomic reference systems and identification protocols and multiplying vouchers. Yet, laboratory information management systems dedicated to multi‐criteria species‐based research are rare or they have not been made openly available to biodiversity professionals. We developed GOTIT (Gene Occurrence and Taxa in Integrative Taxonomy), a database structure and web application for optimizing productivity at various steps of a laboratory's workflow including research project design, sampling gap analysis, sampling planning, species identification, DNA sequencing, information sharing and contributing data to global biodiversity facilities. GOTIT manages the different steps of a species‐occurrence data production process from sampling to sequencing, the storage of specimen lots, slides and DNA extracts and their assignment to morphology‐based and DNA‐based species hypotheses. The application also accommodates species occurrence data and DNA sequence metadata from external sources and the bibliographic referencing of information. GOTIT is designed to optimize research activities on the diversity and evolution of species which have a strong geographic component, such as biogeography and phylogeography. A key feature of GOTIT is the ability to assign multiple species hypotheses based on morphology and molecular delimitation methods to the same set of specimens. This integrative taxonomic approach allows to explore how different aspects of speciation, such as morphological distinguishability and genetic isolation, vary in strength relative to each other across taxa and geographic regions. Another key feature is traceability which promotes repeatability and minimizes duplicate work among multiple users. Any species data refer to a set of localities, sampling methods, biological vouchers, analytical protocols and delimitation methods that can be traced. The application is free and open‐source with extensive documentation and demo version. Developers can reuse the source code or develop new add‐ons to fulfill a laboratory's specific requirements although the application can be used as such to manage species occurrence data for a wide range of taxa.