Pattern

The Pattern instrumentation level represents architectural design patterns applied to data management. Just as software engineering has patterns like MVC (Model-View-Controller) that guide system design, data management has higher-level organizational strategies that guide how datasets, tools, and workflows are composed.

Examples of data management patterns:

YODA (YODAs Organizer of Data Assets) – A pattern for structuring nested datasets with clear separation of inputs, outputs, and code, enabling modular and portable analyses.
BIDS (Brain Imaging Data Structure) – A community standard for organizing neuroimaging data with prescribed directory structures, naming conventions, and metadata files.
Linked dataset graphs – Connecting datasets as a directed acyclic graph of dependencies, so that provenance flows naturally through the structure.

Patterns operate at a higher level of abstraction than individual tools or workflows. They provide a mental model and a set of conventions that make it easier to reason about, communicate about, and maintain complex data management setups over time.

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 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.

Datasette and MVC Pattern for Actionable Data Exploration

19 February 2026·8 mins

Transparency Efficiency Accessible Interoperable Pattern A — Actionable S — Self-contained Datasette Mvc Data-Exploration Sqlite

Shows how datasette turns static datasets into interactive, queryable web applications following an MVC-like pattern.

Ephemeral Shell Scripts for Reproducing Issues

19 February 2026·6 mins

Reproducibility Rigor Transparency Reusable Accessible Pattern S — Self-contained A — Actionable E — Ephemeral P — Portable Shell Posix Reproducer Bug-Report Testing

Distills a common practice among open-source developers: writing throwaway shell scripts that set up a fresh environment, reproduce a problem, and can be shared as actionable bug reports or starting points for test cases.