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This repository contains the technical integrations for the City of Konstanz’s climate data platform. It consolidates diverse sources—e.g., weather stations (DWD and city-operated) Key capabilities include Time series ingestion from official, operational and municipal sources (e.g., DWD, LUBW, BASt, Pegelonline, Eco‑Counter, MobiData BW, MaStR, city stations), Persistence in Timescale/Postgres and exposure via APIs (incl. NGSI‑LD via Stellio/Quantumleap, PostgREST) and dashboards (Grafana), Implementations as Node‑RED flows and Python notebooks; experimental orchestration with Dagster and Airflow. Common stack signals: cloud.

Best for Data teamsyou need transparent storage, processing, querying, or reporting behavior

Skip ifyour required connectors or governance controls are not documentedMore

Open-source alternative toIndependent open-source project
01

What it is

This repository contains the technical integrations for the City of Konstanz’s climate data platform. It consolidates diverse sources—e.g., weather stations (DWD and city-operated) GitHub popularity: 1 stars and 0 forks.

Teams can evaluate Klimadatenplattform within its category while keeping the implementation, license, and repository signals visible. Confirm the official documentation against your exact workflow before treating it as a production dependency.

EU catalogue
Open CodeStandalone/BackendStable
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02

Who it’s for — and when to skip it

Data teams

Use it when you need transparent storage, processing, querying, or reporting behavior.

Skip if your required connectors or governance controls are not documented.

Backend engineers

Consider it when the data model and APIs can remain portable across your infrastructure.

Skip if migration and backup procedures are unclear.

Analytics owners

Evaluate it when access to queries and source code is more valuable than a closed dashboard workflow.

Skip if nontechnical operators require a fully managed support model.

03

Strengths and trade-offs

Why teams consider it

Time series ingestion from official, operational and municipal sources (e.g., DWD, LUBW, BASt, Pegelonline, Eco‑Counter, MobiData BW, MaStR, city stations)

Persistence in Timescale/Postgres and exposure via APIs (incl. NGSI‑LD via Stellio/Quantumleap, PostgREST) and dashboards (Grafana)

Implementations as Node‑RED flows and Python notebooks; experimental orchestration with Dagster and Airflow

Source code and EUPL-1.2 license are visible before adoption

Repository metrics are available for independent review

What to validate

A public repository does not automatically guarantee a documented self-hosting path

GitHub popularity is not a security, quality, or product-fit guarantee

The EUPL-1.2 license still needs review against your distribution and commercial model

Support quality, migration effort, and production hardening vary by project

04

Capabilities and stack fit

01Time series ingestion from official, operational and municipal sources (e.g., DWD, LUBW, BASt, Pegelonline, Eco‑Counter, MobiData BW, MaStR, city stations)
02Persistence in Timescale/Postgres and exposure via APIs (incl. NGSI‑LD via Stellio/Quantumleap, PostgREST) and dashboards (Grafana)
03Implementations as Node‑RED flows and Python notebooks; experimental orchestration with Dagster and Airflow

Catalog metadata supports discovery, not installation. Verify supported versions, dependencies, deployment topology, and production requirements in the official repository.

05

Guides for Klimadatenplattform

No project-specific guide is published yet.

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06

Approved community reviews

No approved review signal yet.

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07

Before you adopt it

  1. 01

    Read the license and confirm it fits your intended use and distribution model.

  2. 02

    Review recent commits, open issues, releases, and the maintainer response pattern.

  3. 03

    Run a small proof of concept with representative data, users, and integrations.

  4. 04

    Confirm whether an official deployment or self-hosting guide exists.

  5. 05

    Document an export or migration path before storing critical data.

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