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ODOMATIC: Automatic Species Identification, Functional Morphology, and Feature Extraction to alleviate the taxonomic impediment and broaden citizen science tools.

The naming and classifying of living organisms is a fundamental principal upon which biology is founded. Indeed, almost every facet of our lives - from the food we eat to the medicine we take, the houses we live in to the natural scenery we admire - has a connection to the biodiversity present on Earth. All species must be named and cataloged in order for humans to understand the world around us. The scientific field of taxonomy, responsible for identifying and describing species, has incurred a reduction in its specialist workforce in recent decades; this is unfortunate because the need for taxonomy has never been greater as human activities result in unprecedented decline in the diversity of life. This project will help to reduce the burden placed on current and future taxonomists to identify and catalog biodiversity by introducing a set of open-source, web-based tools for identifying species from images and for measuring imaged specimens for comparative studies. These software tools will be made freely available through the publicly-funded CyVerse web platform. In addition, a system for identifying dragonflies and damselflies called ODOMATIC will be implemented on an existing web presence, OdonataCentral, allowing researchers and enthusiasts to accurately identify these insects from images of their wings. A series of free workshops will be offered in diverse urban communities in New Jersey and Alabama to increase the diversity of OdonataCentral?s user base, encourage participation in the STEM fields, and generally increase appreciation and understanding of the natural world. A series of Google Hangout events will encourage international user-ship for ODOMATIC from World Dragonfly Association members in Latin America, Africa, and Asia. In addition, undergraduate students from Rutgers University-Newark will be recruited to help in designing and training ODOMATIC, giving them valuable experience in research, programming and taxonomy. This work will help to reduce the taxonomic impediment - an urgent need for more taxonomic products, like species descriptions and specimen identifications, from fewer taxonomist workers - by addressing the time-consuming, but necessary, task that is species identification. Objectives of this project include release of a newly-developed system for automatically identifying Odonata (dragonflies and damselflies) from images of their wings, which uses computer vision and machine learning to characterize and classify species. An interface will be deployed making species identification using this system accessible through the OdonataCentral website (odonatacentral.org). In addition, stand-alone tools will be developed for automatically describing and placing geometric morphometric landmarks on specimens in biological imagery for use in morphology-based comparative studies. The successful completion of these objectives will benefit the odonatological community by providing dragonfly and damselfly identification. More broadly, the tools created here will allow biologists studying other groups of organisms to rapidly extract morphological data from images of their specimens.

Project URL: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1564386

Geographic Scope: Global

Project Status: Active -not recruiting volunteers

Participation Tasks: Annotation, Classification or tagging, Geolocation, Identification, Measurement, Observation, Specimen/sample collection,

Start Date: 2016-09-01

Project Contact: jware@amnh.org

Federal Government Sponsor:

NSF logo

Other Federal Government Sponsor:

Name of Nonfederal Sponsors:

Fields of Science: Animals, Biology, Computers and technology, Pollinators/insects,

Intended Outcomes: Programmatic, Research development, Conservation,