Umbral is an independent, open-source data lab. We build data products, causal analysis, and monitoring tools for the public interest — everything reproducible, everything documented.
umbral (Spanish) = threshold: the point where evidence becomes significant
Projects
Every project publishes its code under the MIT license and its cleaned data under CC BY 4.0. Public data goes back to the public, improved.
In development
A pipeline that turns Mexico's RNPDNO registry of disappeared persons into clean, monthly, per-state CSVs disaggregated by category, sex, and municipality — every raw response cached and reconciled against the official dashboard's totals. A Streamlit dashboard runs on the processed data.
In development
An open, reproducible pipeline for crime incidence, victimization, and perception of safety in Mexico. Immutable vintage-tagged snapshots, rates per 100,000 with CONAPO denominators, and SESNSP–INEGI homicide reconciliation.
Data
Every dataset we publish ships with full provenance: origin URL, download date, license, and known caveats. Every number traces to a scripted transform — never a manual edit. If a figure cannot be reproduced, it is not published.
Methodology
Every chart is titled with its finding, and the finding must be defensible from the data shown. No headline the evidence does not support.
"Associated with" and "correlates" for descriptive work. "Effect" and "reduces" only with an explicit identification strategy, its key assumption stated next to the estimate.
Intervals on projections, confidence intervals on estimates, n and denominator on rates. A point estimate without an interval is incomplete.
The y-axis starts at zero for bars; any truncation is annotated. Missing or underreported data is disclosed — never silently dropped or imputed.
Sensitive topics are handled with dignity: people are counted, never turned into spectacle.
About us
Umbral is built by two people. Everything we publish carries our names and can be audited in the code.
Co-founder
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Co-founder
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