The primary focus of this research is to locate, collate, organize, and format data that will be used in conjunction with multifrequency narrowband (CW), frequency modulated (FM), and lowfrequency…

This Cooperative Agreement award from the National Oceanic and Atmospheric Administration (NOAA) under the Cooperative Institute (Inter-Agency Funded Activities) program (CFDA 11.405) provides $2,316,075.00 in funding to the University of Colorado to support active acoustic and passive acoustic monitoring research. The primary objectives are to: 1) Collate and format annotated acoustic data for advanced analytical echo-classification models; 2) Organize co-variate data for input to these models; and 3) Develop an efficient and scalable workflow to archive a large volume of diverse passive acoustic monitoring (PAM) datasets. This work aims to improve the data preparation and archiving process for NOAA Fisheries scientists to submit their data to the National Centers for Environmental Information (NCEI). The award period runs from September 1, 2024 to August 31, 2027.

The primary focus of this research is to locate, collate, organize, and format data that will be used in conjunction with multifrequency narrowband (CW), frequency modulated (FM), and lowfrequency echosounder data in advanced analytical models to classify active acoustic data to the lowest taxonomic level possible. The models will be developed as part of the echo classification activity within the AA-SI, and we anticipate considerable collaboration among the different teams. Active acoustic objectives: 1. Collate and format annotated acoustic data from the six science centers for input to advanced analytical echo-classification models; 2. Organize CO-variate data for input to advanced analytical echo-classification models; 3. Work collaboratively with the science centers and data scientists/software developers in support of the AA-SI 'echo classification' activity the primary focus of this research is to improve the process for NOAA fisheries scientists to prepare their data for submission to the ncei archive. Currently, the main methodology to capture the necessary metadata fields to describe the datasets and organize files in an consistent structure is to use passivepacker, a windows-based GUI software package. Passivepacker is relatively easy to use, however, the information for each dataset needs to be manually entered. This approach is not practical when considering the volume and number of already existing PAM datasets across NOAA fisheries. A new, scalable and efficient pathway to programmatically capture the necessary metadata and prepare datasets in a standardized manner to submit to ncei will be developed. This work:flow will be flexible to support data hosted on local servers or on the cloud; expansive to support a variety of data collection platforms; and scalable to support the large and rapidly increasing volume of PAM data. Passive acoustic objectives 1. Work collaboratively with the six science centers to determine an efficient pathway to archive a large volume of diverse PAM datasets; 2. Implement an improved archival pipeline that is efficient and streamlined; 3. Archive at least 50% of existing PAM data; and 4. Ensure global access to these archived datasets.