Software discipline

Scientific, Research, and Laboratory Software

Plan scientific systems around samples, datasets, methods, provenance, reproducibility, controlled collaboration, sharing, preservation, and ownership.

Planning this work

Scientific software must preserve meaning across collection, transformation, analysis, review, publication, reuse, and long-term stewardship. A file is useful evidence only when people can determine its subject, method, units, version, provenance, limitations, authority, access conditions, and relationship to results.

These guides cover laboratory operations and research-data collaboration without treating them as one generic repository. They help organizations model samples and datasets, instrument and computational provenance, metadata, quality decisions, access agreements, sharing plans, repository deposits, migration, resilience, and sustainable ownership.

Practical guides in this discipline