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High-frequency sonar systems deployed on a broad variety of ocean observingplatforms are creating a deluge of water column sonar data at unprecedentedspeed from all corners of the ocean. Efficient and integrative analysis ofthese data, either across different sonar instruments or with otheroceanographic datasets, holds the key to monitoring and understanding theresponse of marine organisms to the rapidly changing environments. In thispaper we present echopype, an open-source Python software library designed toaddress this need. By standardizing water column sonar data from diverseinstrument sources following a community convention and utilizing the widelyembraced netCDF data model to encode sonar data as labeled, multi-dimensionalarrays, echopype facilitates intuitive, user-friendly exploration and use ofsonar data in an instrument-agnostic manner. Through leveraging existingopen-source Python libraries optimized for distributed computing, echopypedirectly enables computational interoperability and scalability in both localand cloud computing environments. Echopype's modularized package structurefurther provides a conceptually unified implementation framework for expandingits support for additional instrument raw data formats and incorporating newdata analysis and visualization functionalities. We envision the continueddevelopment of echopype as a catalyst for making information derived from watercolumn sonar data an integrated component of regional and global oceanobservation strategies.

Echopype: A Python library for interoperable and scalable processing of water column sonar data for biological information