📖 Working Draft · v0.1 · 12 May 2026
The Pulse — open methodology
A composite urban wellbeing score across nine SDG-aligned dimensions. Computed from public open data, displayed for any citizen to read. This page documents how it works, what it is honest about, and what we are still building.
Maintainer · Tunç Meriç · cittopia.com/methodology
Status — what this document is
Version 0.1. The methodology described below is in production. It has not yet been independently audited.
The Pulse is good enough to inform civic conversation and demonstrate the platform's intent. It is not yet good enough to back consequential funding or policy decisions. That is what the validation cycle described on this page is for.
We have published this methodology — gaps and all — because civic-tech that hides its limitations is the same problem we set out to solve. Critique, correction and academic challenge are explicitly invited.
01 · Purpose
What The Pulse is — and what it isn't
A composite indicator designed to make European cities readable to citizens, comparable across borders, and accountable to a shared scale of wellbeing.
The Pulse synthesises publicly available open data into a single 0–100 score per city, computed across nine SDG-aligned dimensions and updated as source data refreshes. It is published openly at cittopia.com/explore — every citizen, journalist, mayor or researcher can see the score for any covered city without an account, and can drill into the dimension-level breakdown that produced it.
The intent is civic literacy, not institutional ranking. Composite indicators are politically contested instruments — they aggregate multidimensional phenomena into a single number, which inevitably loses information and can mask substantive trade-offs. We take that critique seriously (see References below). We have nonetheless chosen to build a composite for three reasons:
- Cognitive accessibility — most citizens cannot interpret 350+ Eurostat Urban Audit indicators. A single 0–100 number offers an entry point that invites further drill-down.
- Cross-city comparability — without aggregation, comparing Warsaw to Sofia to Lisbon requires expert mediation. The Pulse provides a first-order comparison anyone can read.
- Accountability surface — a public score, computed transparently from public data, is itself an accountability mechanism. Cities that perform poorly cannot quietly bury the indicators that would show it.
02 · Framework
The nine dimensions
SDG-aligned, drawing on the Stiglitz-Sen-Fitoussi framework (2009), the OECD Better Life Index (2011), and the EU Urban Audit conceptual model.
01
🚇
Mobility & Transit
Transit reach, modal share, congestion, active mobility infrastructure
SDG 11.2
02
🌳
Environment & Air
PM2.5, NO₂, green-space ratio, water quality
SDG 3.9 · 11.6 · 15
03
🏥
Health & Wellbeing
Life expectancy, infant mortality, healthcare access, mental health proxy
SDG 3
04
🏫
Education & Skills
Tertiary education %, NEET rate, library / educational facility density
SDG 4
05
💼
Jobs & Economy
Employment rate, GDP per capita PPP, business density, sector diversity
SDG 8
06
🏘️
Housing & Density
Housing cost as % of income, overcrowding, density, housing quality
SDG 11.1
07
👥
Inclusion & Equity
Gender pay gap, foreign-born integration, Gini, accessibility
SDG 5 · 10
08
🛡️
Safety & Trust
Crime per 1000, perceived safety, clearance rate, trust in police
SDG 16.1
09
🤝
Civic Participation
Voter turnout, Listening Score, Agora activity, civic associations
SDG 16.7
03 · Computation
How it's computed
Three steps: normalise each indicator against the EU cohort, average within each dimension, then aggregate the nine dimensions to The Pulse.
3.1 Normalisation
Each indicator is normalised against the EU cohort using a z-score scaled to a 20-point spread:
# For each indicator i, dimension d, city c:
score(c, d, i) = clamp(0, 100, μ_EU + ((value(c, d, i) − μ_EU) / σ_EU) × 20)
# A city one standard deviation above the EU mean scores 70 on that indicator.
3.2 Indicator → Dimension
Within a dimension, the constituent indicator scores are averaged with equal weights to produce a dimension score in [0, 100]. Where indicators are missing for a city, the dimension score is computed over the available subset, with a coverage flag attached.
3.3 Dimension → Pulse
The nine dimension scores are aggregated to produce the city Pulse:
Pulse(c) = Σ score(c, d) × w(d), where Σ w(d) = 1
# Default weights are equal: w(d) = 1/9 for all d.
# This is a transparent baseline — not a defensible final answer.
# See "Known limitations" below.
3.4 Regional aggregation
For regional Pulse scores (e.g. Mazowieckie Voivodeship), member-city Pulses are aggregated using population weights:
PulseRegion(R) = Σ (Pulse(c) × pop(c)) / Σ pop(c), c ∈ R
04 · Honesty
Known limitations — the v0.2 to-do list
Every composite indicator has methodological choices that can be challenged. We list ours, in plain language, so you don't have to find them by reverse-engineering.
What we know is not yet good enough
- Indicator selection — currently founder-judgement. v0.2 will introduce blind scoring against documented criteria.
- Dimension framework — nine dimensions chosen post-hoc against SDGs. v0.2 should derive (or empirically validate) the dimension structure via factor analysis or expert Delphi.
- Equal weighting — defensible default but not theoretically derived. v0.2 will run weight-perturbation Monte Carlo to test rank stability.
- Linear aggregation — fully compensatory. Bad performance on Health can be offset by good performance on Economy. Munda (2008) and others argue this is inappropriate when dimensions represent qualitatively distinct concerns. v0.2 will compare with geometric and non-compensatory alternatives.
- Normalisation method — z-score makes scores cohort-relative. A city can improve in absolute terms while its score drops because peers improved more. v0.2 will compare with min-max and distance-from-frontier methods.
- Sensitivity analysis — not yet performed. v0.2 will run full Monte Carlo per OECD-JRC Handbook §6, including weight, normalisation, and indicator-set perturbation.
- Uncertainty quantification — current scores are point estimates. v0.2 will produce 95% confidence intervals.
- Sparse data cities — some cities have only ~50 of 350+ indicators populated. The Medium / Low confidence flags help, but the underlying issue is structural to Eurostat. v0.2 will assess imputation methods (or formalise the no-impute stance).
- Civic Participation dimension — heavily dependent on the proprietary Listening Score, which exists only for cities active on Cittopia (small sample). For most cities the dimension currently uses voter turnout alone, which is weak. v0.2 will integrate civic-association density and trust survey proxies.
- Cross-tier comparison — the methodology for comparing a city Pulse to a regional Pulse to a district Pulse is not formally specified. v0.2 will document scaling rules.
- No formal external review — this page, and the white paper linked below, are the first step of that review.
05 · Validation
The validation pathway
Two parallel tracks. Both invited, both honest about The Pulse's current state.
In progress
1. Statistical Audit by JRC Ispra
We have submitted The Pulse for consideration by the European Commission's Joint Research Centre (JRC) — specifically the COIN (Composite Indicators) team in Ispra. The audit covers theoretical framework, indicator selection, normalisation, weighting, aggregation, robustness and statistical coherence.
Authority on EU composite indicators. Same audit applied to the EU Innovation Scoreboard and the Quality of Government Index.
In progress
2. Academic methodology partner
We are seeking an academic co-author from the OECD-JRC Handbook lineage. The partnership scope: a published methodology paper with the academic(s) as co-author(s), and an advisory role on the v0.2 methodology cycle.
First contact: Andrea Saltelli (Universitat Pompeu Fabra / University of Bergen) and active members of his network.
Open invitation
3. Institutional partners
Cities, marshal offices and regional development agencies whose data we surface. The relationship: a feedback loop on data quality, dimension selection, and intended use.
First contact: Mazowieckie Voivodeship · Stefan Batory Foundation · City of Warsaw · Eurocities.
06 · Engage
Download, comment, contribute
If you've read this far, you have something worth saying. We want to hear it.
Read the full white paper
The complete methodology in 12 pages — covering everything on this page in deeper detail, plus the academic references and the v0.2 roadmap.
Send a comment
Substantive critique, missing references, suggested indicators, methodology objections — all welcome. We read every message.
📚
Looking for the technical reference docs?
The Pulse Engine, Eurostat ingestion pipeline, data confidence scoring and SDG mapping live in the deeper documentation hub.
Open the docs →
07 · References
References
- Munda, G. (2008). Social Multi-Criteria Evaluation for a Sustainable Economy. Springer.
- Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., & Giovannini, E. (2008). Handbook on Constructing Composite Indicators: Methodology and User Guide. OECD Publishing.
- OECD (2011). How's Life? Measuring Well-Being. OECD Better Life Initiative.
- Saisana, M., Saltelli, A., & Tarantola, S. (2005). "Uncertainty and Sensitivity Analysis Techniques as Tools for the Quality Assessment of Composite Indicators." Journal of the Royal Statistical Society A 168(2): 307–323.
- Saltelli, A. (2007). "Composite Indicators between Analysis and Advocacy." Social Indicators Research 81(1): 65–77.
- Saltelli, A., & Funtowicz, S. (2014). "When All Models Are Wrong." Issues in Science and Technology 30(2): 79–85.
- Stiglitz, J., Sen, A., & Fitoussi, J.-P. (2009). Report by the Commission on the Measurement of Economic Performance and Social Progress. Paris.
- European Commission (2003 / 2018). Urban Audit: Methodological Handbook. Eurostat.