Gittersubstrat

Gittersubstrat is a conceptual framework for organizing and executing reproducible computational workflows by combining a Git-based versioning model with a substrate-oriented execution environment. It aims to make data, code, and runtime configurations inherently versioned and auditable, enabling traceability from inputs to outputs.

The framework envisages two intertwined layers: a substrate layer that models compute resources, environments and data stores as modular, reusable units; and a git layer that stores workflow definitions, configurations and data lineage as commits in repositories. Workflows are represented as directed acyclic graphs whose nodes correspond to substrate components such as containers, storage, or compute steps. Each node carries versioned parameters and dependencies.

Runs are triggered by changes in the repository and are reproducible because each step executes in isolated, versioned environments. The system records provenance information, including input versions, container images, and parameter values, in an immutable ledger associated with the workflow commit.

Features and capabilities include support for containerized environments (Docker/OCI), modular substrates, explicit data lineage, branching and merging of experimental pipelines, role-based access control, and integration with cloud and on-premises resources.

Applications of Gittersubstrat span data science, bioinformatics, and research computing, where the goal is to enable reproducible analyses, auditability of results, and easier collaboration across teams.

Origins and reception: the term combines "Git" and "substrate" to reflect the idea of a versioned execution substrate. The concept emerged in theoretical discussions of reproducible workflows in the early 2020s. In practice, related systems exist under various names, but Gittersubstrat remains a hypothetical or proposed approach rather than a widely adopted standard.

See also: Reproducible research, Data provenance, Workflow management, Version control.