Provenance and Reproducibility
Use this section to understand how Licklider tracks dataset revisions, analysis context, and the information needed to reproduce a result.
Use Provenance and Reproducibility when your question is how a result can be traced back to the data, settings, and analysis state that produced it.
This section is for checking dataset revisions, provenance records, preprocessing history, and the information needed to reproduce a figure or result. It is not the place to define the dataset structure, plan the analysis rules, or choose the statistical method itself.
What this section helps you decide
Use this section when your immediate question is one of these:
- Which dataset revision was used for a figure or result?
- What preprocessing, exclusions, or configuration changes were applied before the result was generated?
- Which version of the application, statistical engine, or ruleset was involved?
- Whether an earlier result still matches the current
Data Contractand dataset state?
This category is about traceability and reproducibility after setup choices have been recorded. It helps you identify where a result came from and whether it can be recreated under the same conditions.
Read the page that matches your reproducibility question
| If you need to know... | Read this page |
|---|---|
Which dataset revision, preprocessing history, and Data Contract state a figure came from | Versioning and Provenance |
| What the downloadable reproducibility ZIP contains and when it is available | Reproducibility Package |
| How a live project policy is compared against stored figure evidence across the whole project | Project Statistical Policy and Consistency Audit |
Start here
Start with Versioning and Provenance if you need to trace a figure back to its dataset revision, inspect the provenance record, or confirm whether a result was generated under the same assumptions that exist now.
If your question is about the ZIP download itself, including which files are packaged, what manifest.json covers, and how browser-captured exports are disclosed, continue to Reproducibility Package.
If your question is whether all figures in the project still match the current effective statistical policy, continue to Project Statistical Policy and Consistency Audit.
What this section does not cover
- Defining rows, IDs, outcome types, or replicate structure -> see Data Contract
- Declaring hypothesis direction, exclusion rules, or other pre-analysis decisions -> see Analysis Planning
- Choosing file shape, required columns, or import fixes -> see Data Requirements
- Choosing or interpreting a statistical method -> see Methods
Related
- Related links are registered in frontmatter and rendered below this page.