Djinious
Municipal open data · trees, cycle networks, sports facilitiesGeospatial & territory

Municipal asset inventories

Bring the small, messy, locally-published datasets together — and find out which of them can be trusted before you draw them.

DjiniousMap
A dataset detail page reporting that no CRS could be inferred, with a full profile, a Full profile badge, and quality findings for excessive coordinate precision and stale data.

A municipality’s own open data is where CRS problems live: a layer served in Lambert-93 but declared as WGS 84, another with coordinates carrying nine decimal places of false precision, a third whose newest date is from 2005.

The profiler reports each one, with the reasoning and the remediation, and refuses to place the ones it cannot read. That refusal is the feature: a map that silently drew them would put a cycle network in the Gulf of Guinea.

How it runs

  1. Register and materialize

    Register each source and materialize it.

    Harvest
  2. Read the quality card

    Declared vs measured CRS, precision, freshness.

    CRS inference
  3. Decide each finding

    Fix or accept each finding — the platform never silently corrects one.

    Quality findings
  4. Compose what survives

    Compose what survives into one map, with cross-filtering widgets.

    Map studio

Two ways a declared CRS can be wrong