NEB RADAR implements the official EU JRC139118 Self-Assessment Method — no proprietary grading on top.
Every project is scored on the official 0–10 scale across the three values of the New European Bauhaus: Sustainable (climate, ecology, circularity), Beautiful (aesthetic quality, experience, identity), and Together (inclusion, participation, co-creation).
Each pillar score is the mean of its KPIs. NEB RADAR does not compute a single aggregate grade — the official JRC139118 output is the three pillar scores and their corresponding NEB Ambition Levels.
Per JRC139118, each pillar score maps to one of three official Ambition Levels:
JRC139118 defines what to measure — not who has signed off on the data. NEB RADAR adds a separate evidence-trust label so users can tell self-reported entries from independently reviewed ones. This is about data provenance, not grading.
Indicative JRC139118 scores derived from our seed data and AI-assisted assessment. Useful as a starting point — not audited. Most projects start here.
The project lead has claimed the profile and is responsible for adding source citations (reports, KPIs, news articles) backing each pillar score.
A reviewer from the NEB RADAR Advisory Board has examined the evidence against JRC139118 and signed off on the scores.
Each pillar is broken down into KPIs — 9 for Sustainability (S.1–S.9), 6 for Beauty (B.1–B.6), 6 for Together (T.1–T.6). Anyone can re-derive a pillar score by scoring each KPI 0–10 and averaging within the pillar.
If you lead a project listed on NEB RADAR, open its profile and use the Claim this projectbutton. Once approved you can add citations linking each KPI score to a primary source.
Spot an error? Email info@urbanlabs.info. All data is CC0 — see Open Data.
Assessment methodology: EU Joint Research Centre JRC139118 — New European Bauhaus Self-Assessment Method. Scores are 0–10 per indicator across the official 21 KPIs (Sustainability S.1–S.9, Beauty B.1–B.6, Together T.1–T.6). NEB RADAR is a faithful implementation of this official EU tool and adds no proprietary grading layer. JRC publication ↗ · Methodology