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About

Motivation

The reproducibility literature shows that process information is exactly what gets lost when results are shared. Standard task trackers and experiment trackers do not model research phases; nothing records the role of generative AI in the workflow in a machine-readable way.

In the era of AI-assisted research, there is a need for a citable, versionable record that:

  1. discloses the role AI played (cognitive_prosthesis, co_pilot, autonomous_agent), and
  2. anchors each step to verifiable evidence — commits, QPU job IDs, data/code links

so that "how the research happened" is as reproducible as the results themselves.

research-timeline provides that record with a minimal, CI-friendly, schema-validated tool.

Design philosophy

  • Simplicity over power — no database, no cloud, no lock-in
  • Git-native — a single JSON file that diffs cleanly and versionizes with your code
  • Offline-first — works on a plane, in a lab, or in a notebook without network
  • Decades-durable — plain JSON readable by any parser, archived via Zenodo and Software Heritage

How it differs from other tools

  • Notes/task tools (Notion, Obsidian, Logseq, Trello) — no typed research phases, no JSON schema, no CI validation, cloud-bound
  • Experiment trackers (Weights & Biases, MLflow, DVC) — track model runs and artifacts, not researcher-level process events, and no paper-oriented exports
  • Notebooks (Jupyter, Quarto) — rich narrative but unstructured, no schema enforcement, no machine-readable JSON-LD export
  • Lab notebooks (ELN, Code Ocean) — heavyweight, instrument-locked, or cloud-bound

research-timeline fills a specific slot: a provenance instrument for the research process. RETTIFICA (01/09/2026): an earlier claim of uniqueness was retracted - timeline visual tools exist (timeline-fishbone-generator, timeline-maker, SubThesis Timeline Generator, Research-Timeline-Planner, The Timeline Project); this tool differs by design, not by existence.

Credits & provenance

License

MIT — see LICENSE.