Our team of research technicians annotates all of the video from MBARI’s ROV and other select platforms, documenting animal identifications, features, and behaviors along with surrounding habitat characteristics. These observations provide the foundation for novel research that is critical to our understanding of ocean health and our climate system. 

We aim to build capacity for the future by continually advancing our video infrastructure, including our lab facilities, the visual asset management system, annotation workflows, and supporting programs. We provide research, engineering, and processing expertise to build innovative hardware and software programs that support both human- and machine-generated observations for our video observations catalog.

Through continual collaboration with engineers and researchers across the institute, we strive to attain our common goals around visual observation data generation, maintenance, utilization, and dissemination. To further enrich our data and our programs, we also collaborate with colleagues outside of MBARI as a means of sharing our data with and incorporating feedback from the broader research and development communities. 

These stunning visual assets also offer a powerful means of engaging broader audiences and inspiring them to learn more and become ocean champions. To that end, we work in partnership with MBARI’s Science Communication team to produce videos and create other content that utilizes these rich archives to tell compelling stories about our research.



Lemon, L.M., K.L. Smith Jr., and C.L. Huffard. 2022. Abyssal epibenthic holothurians respond differently to food quantity and concentration fluctuations over a decade of daily observation (2007 ̶ 2017). Deep-Sea Research I, 188(103853): 1–10. https://doi.org/10.1016/j.dsr.2022.103853

Cochrane, G.R., L.A. Kuhnz, L. Gilbane, P. Dartnell, M.A.L. Walton, and C.K. Paull. California Deepwater Investigations and Groundtruthing (Cal DIG) I, Volume 3—Benthic Habitat Characterization Offshore Morro Bay, California. Reston, VA: 2022. https://doi.org/10.3133/ofr20221035

Kuhnz, L.A., L. Gilbane, G.R. Cochrane, and C.K. Paull. 2022. Multifactor biotopes as a method for detailed site characterization in diverse benthic megafaunal communities and habitats in deep-water off Morro Bay, California. Deep Sea Research Part I: Oceanographic Research Papers, 190(103872): 1–19. https://doi.org/10.1016/j.dsr.2022.103872

Boulais, O., B. Woodward, L. Lundsten, K. Barnard, B. Schlining, K.C. Bell, and K. Katija. 2020. FathomNet: An underwater image training database for ocean exploration and discovery. arXiv: 2007.00114. https://doi.org/10.48550/arXiv.2007.00114

Katija, K., B. Schlining, L. Lundsten, K. Barnard, G. Sainz, O. Boulais, B. Woodward, and K.L. Croff Bell. 2021. FathomNet: An open, underwater image repository for automated detection and classification of midwater and benthic animals. Marine Technology Society Journal, 55(3): 136–137. https://doi.org/10.4031/mtsj.55.3.20

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