Within the essential data acquisition (EDA) component of the IRA, data GAP mitigation and application of advanced technologies were identified among multiple priorities

The EDA component established subcomponents, which included improvements to territorial and tribal data acquisition and strategic initiatives (SIS) in seven advanced technology and social science fields. At NOAA fisheries southeast fisheries science center (sefsc), the territorial/tribal data acquisition, passive acoustics SI (PA-SI), active acoustics SI (AA-SI), remote sensing SI (RS-SI), and optics SI (OP-SI) subcomponents seek new expertise from NOAA cooperative institutes to further research in data-poor areas and fields of advanced technologies. The goals of this project are multifaceted and include: 1) territorial/tribal data acquisition seeks to reduce gaps in data critical to inform stock assessment and resource management in the US caribbean. Support of territorial projects will be provided through cimas to: continue work on the classification of caribbean benthic habitats, estimate fishing effort using remote sensing data; coordinate and integrate existing fishery independent survey work currently ongoing (or planned) among numerous federal, territorial, and academic organizations; and develop AI/machine learning to improve fishery independent queen conch surveys. 2) passive acoustics SI seeks to advance passive acoustic monitoring technologies to achieve four transformational and national goal oriented projects that improve our ability to access ocean sounds to inform marine species and climate trends. The projects focus on: establishing a pacific region glider program to mirror that in the atlantic; developing national cloud capabilities to cope with exponential growth in data and processing needs; expanding an existing decision support tool to a national level tool; and streamlining analytical and data integration to remove redundancy and increase efficiencies. 3) active acoustics SI seeks to revolutionize echo classification by developing processing techniques and building a cloud-based framework that will promote development and implementation of advanced analytical methods to classify backscatter from echosounder datasets. The project seeks to develop advanced analytical methods that are needed to significantly advance echo classification through the combination of high-resolution echosounder, modeled-backscatter, and habitat data; and generate a toolbox of advanced analytical tools for echo classification in the cloud. 4) the remote sensing strategic initiative is dedicated to enhancing the effectiveness and utility of the extensive remote sensing, modeling, and direct observational data amassed by NOAA and its partners. This initiative aims to equip NOAA vessels with new instrumentation and harness satellite data to enhance and automate dynamic oceanographic and species distribution models. 5) the optics strategic initiative will make significant investments to transform nmfss approach to optical data collection and processing. The project seeks to operationalize large-scale image collection, storage, and processing; complement, optimize, and replace existing ship- and aircraft-based surveys; automate and optimize data processing pipelines; and provide novel, mission-improving metrics. The project will develop a suite of transformational technologies that enable end-to-end automation of optical sampling methods.