DARC Data

University of Hawaiʻi Deep-Sea Animal Research Center (DARC) employs a structured, end-to-end annotation workflow designed to create FAIR (Findable, Accessible, Interoperable, and Reusable) high-quality, integrated deep-sea imagery data products to support biodiversity and biogeographic research, ecosystem assessment, and emerging machine-learning applications.

The deep-sea still and video imagery collected by human occupied vehicles (HOVs), remotely operated vehicles (ROVs) and baited stationary cameras are annotated using the Video Annotation and Reference System (VARS) developed by the Monterey Bay Aquarium Research Institute (MBARI) and Tator developed by CVision. Annotations capture animal occurrences and numbers with georeferenced species-level identifications, habitat context, and behavioral interactions. Following annotation, quality control procedures include internal image review, validation against established knowledge bases, external consultation with taxonomic experts, and metadata validation to comply with archival requirements. Datasets are formatted to align with Darwin Core controlled vocabularies, standardized national database schemas, and cross-referenced with the World Register of Marine Species (WoRMS).

The final products hosted below are also archived and submitted to partner programs and repositories, including NOAA's Deep Sea Coral Research and Technology Program, National Geographic Society's Pristine Seas program, Ocean Networks Canada SeaTube, Fathomnet, and NOAA Ocean Exploration Benthic Animal Guide.