Real catalog base
The current public site analyzes selected open data catalogs from around the world rather than using a fictional sample.
Open data value layer
Open Data Value
Open Data Value is a public exploration layer that analyzes real open data catalogs and shows what sits beyond dataset lists: data products, use cases, value graphs, analysis, and AI-agent-ready resources. It demonstrates how open data can become structured value portfolios that people and agents can inspect, compare, and reuse.
Visit Open Data Value1Open catalogs
2Data products
3Use cases
4Value graphs
5Agent resources
From open datasets to product, graph, analysis, and AI-agent-ready context.
What this covers
A public value layer that analyzes open data catalogs and turns datasets into data products, use cases, value graphs, insights, and AI-agent-ready resources.
The work starts from existing public open data portals and reframes them through a product and value lens. Instead of stopping at datasets, Open Data Value organizes catalogs into candidate data products, potential use cases, relationships, portfolio signals, and structured resources for AI-assisted discovery.
Product and use-case lens
Published datasets are translated into candidate data products, potential use cases, and portfolio-level signals.
Value Graph
Relationships between catalogs, datasets, products, use cases, and objectives are exposed as a graph that can support exploration and comparison.
Agent-ready resources
The material is structured so AI agents and developers can use the open data context instead of reading a flat catalog page.
Public learning layer
Open Data Value is a demonstration and discovery environment for showing how open data can move toward usable public value.
01Open data reframed
Catalogs become easier to inspect through products, opportunities, relationships, and practical value signals.
02Portfolio visibility
Different portals can be compared through common dimensions such as data products, use cases, graph richness, and analyzed datasets.
03Agent context
Structured resources make it easier for AI assistants and developer agents to reason over public open data material.
04Adoption example
The site gives open data teams a visible example of how catalog assets can become product and value portfolios.
Related work