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InfraFabric IF.TTT • Traceable, Transparent, Trustworthy
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Sciences

Reproducibility is governance

Scientific trust fails on provenance: datasets, methods, and claims lose their lineage. IF.TTT makes the lineage verifiable — not just described.

Pain points (today)

  • “Which version produced this result?” becomes guesswork.
  • Methods drift; evidence lives in scattered notebooks and drives.
  • Peer review stalls when artifacts aren’t portable and verifiable.

What IF.TTT makes easier

  • Bind inputs to outputs with cryptographic hashes.
  • Publish receipts that reviewers can verify without access to your lab systems.
  • Package evidence in offline bundles for reproducibility and dispute resolution.

Debate extracts (roles)

Principal investigator
“If it can’t be reproduced, it can’t be trusted — even if it’s true.”
Data engineer
“Tell me which inputs, which code, which run. Not a story.”
External reviewer
“Give me a bundle I can verify offline. Then we can talk about the claim.”

Open verification

  • Receipts are designed to be legible: hashes, signatures, and stable URLs.
  • HTML fallbacks exist for constrained reviewer environments.
  • Start with the public IF.TTT explainer: infrafabric.io/static/hosted/ifttt/
if.ttt
what third parties can verify
  1. 1
    Ingest a source
    PDF • policy • dataset • report
  2. 2
    Mirror + claim register
    keep the evidence payload intact
  3. 3
    Bind with a trace
    hashes • signatures • provenance ID
  4. 4
    Publish public receipts
    no login • stable URLs • HTML fallbacks
  5. 5
    Optional triage bundles
    lightweight • standard • full
  6. 6
    Offline verify
    verify with `iftrace.py`
Outcome: a receipt surface third parties can verify without trusting you.
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