Decision-support readiness assessment

The problem

Decision-support platforms are easy to over-specify: projects often start with a platform choice rather than a clear decision to support. Organisations then discover late that key data is missing, too coarse or not updated often enough, or that the in-house team cannot maintain what was built. A short, honest assessment up front avoids that.

What you get

• A list of the decisions and users the system should serve, with priorities
• A data audit: what observations, satellite products and model outputs exist, their coverage, update frequency, quality and access terms
• A gap analysis covering data, infrastructure and staff skills
• A recommended architecture (ingestion, storage, data services, analytics, interface) using open standards such as OGC web services; 3D city models (CityGML/3D Tiles) or sensor APIs (OGC SensorThings) are recommended only where the use case needs them
• A phased roadmap with a minimal first release, indicative effort and risks
• Optionally, a small proof of concept on one data stream

How it works

1. 1

   Discover

   Interviews and a workshop with programme staff, scientists and IT to agree which decisions matter and who will use the system.

2. 2

   Audit

   Inventory and test the available data sources and existing systems, including how current and reliable each one really is.

3. 3

   Design

   Draft an architecture and phased roadmap sized to the available data, budget and maintenance capacity.

4. 4

   Review and recommend

   Present findings, revise with the team, and deliver a written report that can also serve as the basis for terms of reference or a funding proposal.

Tools

• Python
• Google Earth Engine
• PostgreSQL/PostGIS
• GeoServer / THREDDS
• QGIS