The following reference docs provide instructions for common tasks and workflows in Song:
Whether you're new to these tools or looking to refresh your understanding, this glossary is here as a reference of key terms and concepts.
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Analysis: A trackable unit of data in Song that combines metadata and associated data files. It's the main entity in a Song database.
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Analysis ID: A unique identifier (UUID) assigned to each analysis in Song. It's used to track, retrieve, and manage specific analyses throughout the Song and Score.
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Analysis State: The current status of an analysis in Song. States include PUBLISHED, UNPUBLISHED, and SUPPRESSED.
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Analysis Type: A category of analysis defined by Song administrators, which describes the structure and content of a particular kind of data submission.
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Dynamic Schema: A JSON-based schema that defines the structure and constraints of an analysis type in Song.
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Manifest: A file generated by Song that establishes a link between an analysis ID and the data files on your local system, used by Score for file uploads.
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Metadata: Data that describes other data. In the context of Song, it refers to the information about data files included in an analysis.
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Payload: A formatted set of metadata conforming to a specific analysis type schema, submitted to Song as part of the data submission process.
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Score: A file transfer and storage system designed to work alongside Song for managing large data files.
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Song: A metadata management system used to track and manage metadata related to files in a data repository.
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Study: A collection of analyses in Song, typically representing a coherent set of data for a particular research project or data submission.
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Published Analysis: An analysis in Song that has been marked as ready for downstream processing and is searchable within the system.
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Unpublished Analysis: An analysis in Song that has been created but is not yet ready for downstream processing or searching.
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Suppressed Analysis: An analysis in Song that has been temporarily hidden or removed from active use, typically due to data quality issues or other concerns.