M — Modular

Rather than managing a research object as one indivisible whole, STAMPED promotes a compositional approach: independently versioned modules (input datasets, processing scripts, computational environments) can be updated or replaced separately, minimizing disruption and maximizing reusability.

An idiomatic layout delineates components into structured directories – code/, inputs/, envs/, docs/, results/ – clarifying how they interact and supporting domain-specific standards (e.g., BIDS). Components may be included directly or linked as subdatasets (git submodules), each with its own independent version history.

See the STAMPED paper for the full treatment.

Walkthrough: stellar distances from Gaia parallax

12 March 2026·14 mins

Reproducibility Rigor Transparency Reusable Accessible Workflow S — Self-contained T — Tracked A — Actionable M — Modular P — Portable E — Ephemeral D — Distributable STAMPED-intro gaia parallax walkthrough python datalad make

Incrementally builds a research object from a bare script to a tracked, portable, reproducible pipeline — motivated by real problems, not by acronym order.

From Script to STAMPED Research Object

20 February 2026·9 mins

Reproducibility Rigor Transparency Reusable Accessible Pattern S — Self-contained T — Tracked A — Actionable M — Modular P — Portable E — Ephemeral D — Distributable STAMPED-intro shell POSIX awk make git singularity containers

Four scenarios showing how to incrementally add STAMPED properties to a shell-based analysis using git, make, and singularity.

Git Submodules for Modular Dataset Composition

19 February 2026·6 mins

Reproducibility Rigor Interoperable Reusable Tool M — Modular T — Tracked git submodules dataset-organization

Demonstrates how git submodules enable independent versioning and composition of dataset components.