Lage.Bonn Evaluation

Product KPIs

Window: 7d · Generated:

Trends compare 24h cohorts derived by differencing the 1d/2d/3d windows: they measure the items that arrived in each bucket, not the KPI as it read 24h ago. Backfill lands in the cohort of its own timestamp, so the two diverge. Panel values above still reflect the selected 7d window.

Localizability

58%
24h ↑ +16.8pp 48h ↑ +22.1pp

Ortsteil-precise (317 / 551 items)

Bezirk-or-better 79%
Bonn allgemein 60
Umland (neighbor) 52

Cross-source binding (dedup layer)

0%
24h ↓ -2.9pp 48h → 0.0pp

1 / 363 clusters (cluster_id)

Multi-source events (event-graph layer)

6%
24h ↓ -14.3pp 48h ↓ -8.3pp

15 / 246 confirmed events (item_guids)

Item coverage 54%
Uncorrelated 12%
Categorized 100%
Avg / max members 1,22 / 11

Cluster compression

1.52×
no trend

items per effective cluster

Ortsteil coverage

82%
no trend

41 / 50 Ortsteile

Source freshness

36↑ / 36 sources
no trend

Max staleness: 5h 33m · Fail count: 0

Civic responsibility

66%
24h ↑ +33.3pp 48h ↑ +12.1pp

52 / 79 Anliegen resolved to a responsible Akteur. Mapping is partial by design — only bonnorange-attributable service codes resolve today, so this is not a coverage measure.

Anliegen in window 79
Unresolved 27
Without service_code 0 (0%)
Distinct service codes 10

Deep analysis (LLM-backed)

100%
24h — n/a 48h — n/a

8 / 8 qualifying events — confirmed, ≥3 distinct sources (source_id) in window. Not all events.

No analysis at all 0
Deterministic only 0
Unpublished (excluded) 0

Geometry breakdown (by geo_source)

geo_source Count Share
coord 223 40%
text 166 30%
none 60 11%
neighbor 52 9%
street 48 9%
nominatim 2 0%

Anliegen breakdown (by service_code)

Sizes the responsibility mapping from the live store (lage-p6pi.2). A window dominated by <none> means the stored items carry no service_code, not that the mapping is short — the two need different fixes. It does not mean the source dropped the field: anliegen.bonn.de was measured clean on 2026-08-14 (354/354 open records carried a code), so a spike points downstream of the fetch (lage-pjm3).

service_code Count Share
1.5 47 59%
2.3 15 19%
3.1 5 6%
3.2 3 4%
3.4 3 4%
3.3 2 3%
2.5 1 1%
2.7 1 1%
3.5 1 1%
3.7 1 1%