From Script to STAMPED Research Object
·9 mins
Four scenarios showing how to incrementally add STAMPED properties to a shell-based analysis using git, make, and singularity.
Transparency
Transparency means that the research process is open and comprehensible to others (and to your future self). A transparent project makes it clear:
- What data was collected or used.
- How it was processed, transformed, and analyzed.
- Why particular decisions were made along the way.
- Where the data and code can be found.
STAMPED principles support transparency through detailed provenance records, human-readable metadata, public version control histories, and well-documented data organization. When every step of a research project is recorded and accessible, collaborators and reviewers can follow the entire chain from raw data to published results. Transparency builds trust and enables meaningful peer review of not just the conclusions, but the process that produced them.
Datasette and MVC Pattern for Actionable Data Exploration
·8 mins
Shows how datasette turns static datasets into interactive, queryable web applications following an MVC-like pattern.
Ephemeral Shell Scripts for Reproducing Issues
·6 mins
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.
Recording Computational Provenance with datalad run
·6 mins
Shows how datalad run wraps arbitrary commands to record inputs, outputs, and the exact command in machine-reexecutable form.