The following section documents the relationship of this record to the full Eclipse Soundscapes (ES) data lifecycle, a multi-stage workflow designed to support large-scale participatory science, long-term data stewardship, open science, and scientific reuse. Each stage addressed a different operational need, beginning before eclipse deployment and continuing through validation, public archiving, and scientific analysis. Together, these stages transformed distributed volunteer-submitted audio recordings into structured, documented, publicly accessible NASA-funded research assets. Stage 0: Pre-Eclipse Infrastructure and Deployment Preparation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Pre-Eclipse Infrastructure and Deployment Preparation (Stage 0). Zenodo. https://doi.org/10.5281/zenodo.20413370 Stage 0 focused on building the operational foundation required to support geographically distributed eclipse data collection at national scale. This stage included AudioMoth device preparation, accessibility modifications, ES ID # assignment systems, metadata collection workflows, participant training materials, deployment logistics, and planning for downstream data stewardship and archival workflows. The 2023 annular eclipse served as both a scientific investigation and a large-scale operational beta test that informed improvements for the 2024 total solar eclipse campaign. Related Citations and Resources: Severino, M., Winter, H., & Bauer, D. J. Eclipse Soundscapes Apprentice Role Training and Learning Manual (2023–2024). Zenodo. Severino, M., Winter, H., & Bauer, D. J. Eclipse Soundscapes Observer Role Training and Resources Manual (2023–2024). Zenodo. Severino, M., Winter, H., & Bauer, D. J. Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. Stage 1: Receipt, Sorting, and Metadata Organization Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Receipt, Sorting, and Metadata Organization (Stage 1). Zenodo. https://doi.org/10.5281/zenodo.19471425 Stage 1 transformed returned participant materials into organized, traceable site-level records. This included receiving mailed microSD cards, consolidating participant-submitted metadata, reconciling handwritten and online records, organizing physical audio media by ES ID #, and deriving eclipse timing and coverage information using NASA eclipse prediction datasets. The outputs of Stage 1 established the structured metadata relationships required for downstream validation, processing, archiving, and analysis workflows. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). EPTT (Eclipse Phase Timing Tool) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-Eclipse-Phase-Timing-Tool Espenak, F. (n.d.). Eclipse predictions by Fred Espenak, NASA’s GSFC Eclipse Web Site. NASA Goddard Space Flight Center. http://eclipse.gsfc.nasa.gov/eclipse.html Stage 2: Data Processing and Validation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Data Processing (Stage 2). Zenodo. https://doi.org/10.5281/zenodo.18683402 Stage 2 focused on centralized audio ingestion, validation, timestamp verification, metadata reconciliation, and preparation of datasets for analysis and public sharing. During this stage, returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES and ES AMES. The project implemented scalable infrastructure capable of processing large volumes of participant-submitted microSD cards while preserving all raw audio data without modification. Stage 2 established the validated dataset structure required for long-term preservation and scientific analysis. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-WAV-Audio-Validation-Extraction-Suite Winter, H., & Goncalves, J. (2026). ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-AMES-AudioMoth-Metadata-Extractor-Suite Stage 3: Public Data Sharing and Open Archiving Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Public Audio Data Sharing (Stage 3). Zenodo. https://doi.org/10.5281/zenodo.18683437 Stage 3 transformed validated site-level datasets into publicly archived, DOI-assigned research records published through the Eclipse Soundscapes Zenodo Community. This stage included dataset packaging, metadata standardization, README generation, integrity verification, DOI assignment, and automated repository upload workflows using the Automated Zenodo Upload Software (AZUS). These workflows established the project’s long-term open-science infrastructure and ensured that datasets remained findable, accessible, interoperable, reusable, and citable for future scientific and educational use. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). AZUS (Automated Zenodo Upload Software) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/AZUS-Automated-Zenodo-Upload-Software Stage 4: Scientific Analysis and Research Use Stage 4 involves the scientific analysis and interpretation of validated eclipse soundscape datasets. Analysis workflows utilized datasets verified during earlier stages to investigate eclipse-related environmental and animal vocalization changes across hundreds of recording sites. This stage also includes broader scientific interpretation, publication development, and continued reuse of Eclipse Soundscapes datasets and infrastructure for future research, education, and open-science applications. Related Citations and Resources: Pease, B., Gilbert, N., & Severino, M. (2026). Eclipse Soundscapes Preliminary Findings – How Eclipses Affect Nature as determined by Sound (Recorded Webinar). Zenodo. https://doi.org/10.5281/zenodo.18613979 Gilbert, N. A., Pease, B. S., Severino, M., & Winter, H. III. (2026). Photic niche explains avian behavioral responses to solar eclipses. Ecology and Evolution, 16(2), e73090. https://doi.org/10.1002/ece3.73090 Analysis code repository: https://github.com/BrentPease1/eclipse-traits Companion Zenodo record archiving structured analysis scripts and derived outputs: https://doi.org/10.5281/zenodo.15790879 Public Archiving, Privacy, and Data Transparency The Eclipse Soundscapes Data Collector Role Training and Resources Manual includes a detailed explanation of how Eclipse Soundscapes audio data are publicly archived on Zenodo, how participant privacy is protected through the ES ID system, and how transparency and traceability are maintained. It also outlines the criteria used to determine which recordings are included in the public archive and the distinction between publicly shared archival datasets and datasets used for ES-led scientific analyses. Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443

This record documents the Stage 2 data processing and validation workflows developed by the Eclipse Soundscapes (ES) project to support scalable ingestion, verification, documentation, and preservation of large-scale volunteer-collected eclipse audio datasets. The included workflow diagram (“Eclipse Soundscapes Data Process Workflow”) provides a visual overview of the complete ES data lifecycle (Stages 0–4), while this record documents specifically the workflows used to validate, process, organize, and prepare returned audio datasets for downstream public archiving and scientific analysis. Stage 2 focused on centralized ingestion and validation of participant-submitted audio recordings following the receipt, sorting, and metadata organization workflows completed during Stage 1. The workflows described in this record were designed to support scalable processing of large volumes of returned microSD cards while preserving raw audio integrity, documenting timestamp conditions, validating metadata relationships, and maintaining traceability between recordings, devices, and site-level records associated with ES ID numbers. Stage 2 workflows included: centralized ingestion and processing of participant-submitted microSD cards automated extraction and validation of AudioMoth metadata device-to-site verification using ES ID # relationships timestamp plausibility validation relative to eclipse timing windows human-in-the-loop review of incomplete or invalid timestamp records metadata reconciliation and documentation of participant-provided timing information preservation of raw WAV audio files without modification creation of structured backup systems and SHA-512 integrity verification records identification of datasets suitable for downstream scientific analysis workflows preparation of validated datasets for Stage 3 public archiving workflows Returned audio recordings were processed using custom open-source software developed by the ES team, including ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) and ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite), operating within centralized Linux-based ingestion and storage infrastructure designed to support scalable parallel processing workflows. These workflows established the validated, documented, and traceable dataset structure required for long-term preservation, DOI-based public archiving, and downstream scientific analysis within the Eclipse Soundscapes data lifecycle.

This record documents the Stage 2 Data Processing and Validation workflows developed by the Eclipse Soundscapes (ES) project to support scalable, traceable, and reproducible processing of large-scale volunteer-collected eclipse audio datasets. ES distributed AudioMoth devices during the 2023 annular and 2024 total solar eclipses to investigate how rapid eclipse-related light changes influence animal behavior and environmental soundscapes. Stage 2 focused on validating, organizing, and documenting returned audio datasets after physical receipt and metadata reconciliation in Stage 1. This included centralized ingestion of participant-submitted microSD cards, device-to-site verification, timestamp validation, metadata extraction, integrity preservation, and identification of datasets suitable for downstream scientific analysis and public archiving. Returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) and ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite). All raw audio files were preserved without modification while validation outcomes, timestamp conditions, and metadata relationships were documented within structured site-level records. By documenting the scalable processing, validation, and provenance workflows used to prepare Eclipse Soundscapes datasets for long-term preservation and scientific reuse, this record supports transparency, reproducibility, and responsible stewardship of large-scale participatory science data.

General Eclipse Soundscapes Project Information The Eclipse Soundscapes Project (ES) was a NASA Volunteer Science project funded by NASA Science Activation that studied how solar eclipses affect life on Earth during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. ES revisited a historic study from the early 1900s demonstrating that animals respond to eclipses and used modern technology and public participation to expand that research. Eclipse Soundscapes was an enterprise of ARISA Lab, LLC and was supported by NASA award No. 80NSSC21M0008. Any opinions, findings, conclusions, or recommendations expressed in project materials are those of the authors and do not necessarily reflect the views of the National Aeronautics and Space Administration. Foundational Historical Reference: Wheeler, W. M., et al. (1935). Observations on the Behavior of Animals during the Total Solar Eclipse of August 31, 1932. Carnegie Institution of Washington.

This Zenodo record documents Stage 2 of the Eclipse Soundscapes (ES) data lifecycle: the centralized ingestion, validation, metadata extraction, timestamp verification, and preservation workflows used to process large-scale volunteer-collected eclipse audio datasets.