Build an SDG Country Scorecard from UN Data

A country scorecard compresses many indicators into a readable view, but the compression creates methodological risk. Units, directions, years, and data nature differ across UN series. The UN SDG Indicators Scraper supplies the official evidence layer without pretending that one formula fits every goal.

Define the metric registry

Create review examples before publishing scores: a country with full coverage, one with sparse coverage, and one with conflicting years or dimensions. Those cases test whether the interface communicates uncertainty instead of rewarding whichever country happens to report the most data.

For each chosen series, record whether higher is better, target or benchmark, preferred disaggregation, acceptable data nature, and maximum age. Then collect the relevant country and year range.

{"seriesCodes":["SI_POV_DAY1","SI_POV_EMP1"],"areaCodes":["840","356"],"yearFrom":2015,"yearTo":2026,"maxResultsPerSeries":250}

Select a common comparison year when possible. If countries have different latest years, show them rather than hiding the mismatch. Preserve units, dimensions, footnotes, and source alongside any normalized score. Modeled and country-reported values may both be valid but should not be mixed without a policy.

Calculate goal summaries downstream and version the formula. A change to weights, imputation, direction, or scaling should create a new methodology version, not overwrite historical scores. Publish coverage counts next to performance so users can distinguish weak results from weak evidence. Keep the raw UN row and source URL accessible from each scorecard cell. This turns the scorecard into an explainable analytical product rather than an opaque ranking detached from the official data.