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Data Certification Quickstart

Data certification is the IINTS trust layer for validating data quality before modeling or evaluation.

Before this page: Getting Started if you have not produced a run or dataset yet.

After this page: MDMP Guide for deeper certification details, or Scientific Workflow to use certified data in studies.

Use a Virtual Environment

Run all commands from an active .venv: python3 -m venv .venv && source .venv/bin/activate

What Certification Produces

  • Contract validation results (pass/fail per rule)
  • Compliance score
  • Deterministic dataset + contract fingerprints
  • Trust grade: draft, research_grade, or clinical_grade

1) Generate a Contract Template

iints data certify-template --output-path data_contract.yaml

Edit the contract to match your dataset schema and bounds.

2) Validate a Dataset

iints data certify data_contract.yaml data/my_cgm.csv --output-json results/certification.json

Strict mode for pipelines:

iints data certify data_contract.yaml data/my_cgm.csv \
  --min-mdmp-grade research_grade \
  --fail-on-noncompliant \
  --output-json results/certification.json

3) Generate an Audit Dashboard

iints data certify-visualizer results/certification.json --output-html results/mdmp_dashboard.html

This creates a single-file HTML report that can be shared offline.

4) Create Synthetic Mirror Data

iints data synthetic-mirror data/my_cgm.csv data_contract.yaml \
  --output-csv data/synthetic_mirror.csv \
  --output-json results/synthetic_mirror_report.json

Use this for safe development/testing when real data access is restricted.

Grade Interpretation

  • draft: schema partially valid, not ready for rigorous research workflows.
  • research_grade: acceptable quality for research experiments.
  • clinical_grade: strongest validation profile available in the SDK.

Python Gate (Optional)

import pandas as pd
from iints import mdmp_gate

@mdmp_gate("contracts/clinical_mdmp_contract.yaml", min_grade="research_grade")
def process(df: pd.DataFrame) -> int:
    return len(df)

This blocks or warns if input data does not meet required quality.

Important Scope

MDMP improves data quality and traceability. It does not provide clinical approval.

Where To Go Next

If you want to... Continue with
run a benchmark with certified data Scientific Workflow
learn the full MDMP model MDMP Guide
import real-world data first Getting Started
diagnose data command errors Troubleshooting
find related commands Command Reference