Explore open data beyond datasets

We analyze selected open data catalogs from around the world and turn them into data products, use cases, relationships and AI-agent-ready resources.

Real catalogs
Based on public data from around the world
Value perspective
Products, use cases, graphs and insights
AI-agent ready
Structured, interoperable resources for tomorrow
44
portals
714
data products
16,919
datasets analyzed
1,119
potential use cases

The collection grows as more open data portals are added to the shared ecosystem. Join today!

44 trusted open data catalogs from around the world

Ajman Ajman Bahrain Bahrain Bologna Bologna Basel-Stadt Basel-Stadt Long Beach Long Beach Northern Powergrid service area Northern Powergrid United Kingdom UK Government Data Switzerland opendata.swiss Canada Open Government Canada Australia data.gov.au Argentina datos.gob.ar Ireland data.gov.ie Croatia data.gov.hr Boston Analyze Boston Vancouver Vancouver Open Data Portugal Portugal SNS Transparency Portal North West England Electricity North West Paris Paris Open Data Nantes Nantes Metropole Rennes Rennes Metropole Ile-de-France Ile-de-France Open Data France SNCF Open Data Paris Region RATP Open Data France Open Data Reseaux Energies Toulouse Toulouse Metropole Strasbourg Strasbourg Open Data France French Higher Education Open Data France French Education Open Data Pays de la Loire Pays de la Loire Open Data Ontario Ontario Data Catalogue British Columbia British Columbia Data Catalogue Quebec Donnees Quebec Uruguay Uruguay Open Data Japan Japan data.go.jp Global Humanitarian Data Exchange London London Datastore Chile Chile Datos Gob Ukraine Ukraine Open Data Romania Romania Open Data Barcelona Barcelona Open Data Malaga Malaga Open Data Israel Israel Data Gov Slovenia Slovenia OPSI Latvia Latvia Open Data Get your catalog to be included

Leading value portfolios in the collection

A quick view of the portfolios that currently stand out across key dimensions.

Largest analyzed sample

Bologna

704

datasets analyzed

Largest processed dataset set in the current capped intake

Most data products

Bahrain

31

data products

Strongest product candidate portfolio so far

Most use cases identified

Bahrain

49

potential use cases

Broadest use-case coverage currently identified

Richest graph

Australia

992

relationship links

Most connected Value Graph in the collection

Explore Open Data Value Portfolios

API-based portfolio

Ajman

Transforms published datasets into data products, potential use cases, connected graphs and AI-agent-ready resources.

211
Source datasets previewed
10
Catalog domains
13
Data products
13
Preview use cases

Includes public Huwise API and Assistant

Explore

More than datasets

Each catalog analysis creates a comprehensive, interoperable resource collection for people and AI agents.

  1. Value Catalog

    Datasets reorganized around products, uses and relationships.

  2. Data Products

    Data products derived from available catalog evidence.

  3. Use Cases

    Potential applications showing how existing data might be used.

  4. Value Graph

    Connections between datasets, products, use cases, domains and publishers.

  5. AI-Agent Resources

    ODPS family and agent-first machine-readable files for direct consumption.

  6. Analysis

    Findings, gaps, opportunities and prioritized next actions.

One catalog for two audiences

The same catalog transformation provides a rich experience for people and a structured, AI-agent-ready resource collection for machines.

Explore, understand and make decisions

  • CatalogBrowse transformed datasets
  • GraphExplore relationships
  • AssistantAsk questions about the catalog
  • AnalysisReview findings and opportunities

Consume and integrate

  • ODPS / ODPC / ODPG / ODPVStandardized interoperable structures
  • Agent-ready filesJSON, YAML and graph resources
  • Structured metadataProducts, use cases and relationships
  • Ready for AI workflowsUse in agents, applications and pipelines

Ask your Value Portfolio

Get answers, discover data products and use cases, and explore relationships grounded in real open data from this portfolio.

  • Ask in your own languageVoice or text, including Arabic
  • Choose a perspectivePolicy, business, technical or general
  • Grounded in this portfolioData products, use cases, relationships and more
  • Go from question to actionExplore, compare and reuse
AI Assistant
EN
General Policy Business Technical

Which datasets support real estate investment analysis?

The strongest combination includes transaction activity, mortgage data, real estate offices and district-level geographic data.

  • 5 relevant datasets
  • Related data products
  • Potential use cases
  • View in graph
Ask a question...

Speak or type in your preferred language, including Arabic

Open data ready for AI agents

We provide structured, interoperable resources for AI agents, APIs and workflows, built from catalog metadata, datasets, data products, use cases and graph relationships.

  • Support
    data reuse
  • Enable
    AI innovation
  • Built on
    open standards
  1. 01 Catalog metadata

    Structured and machine-readable information about datasets, publishers and domains.

  2. 02 Datasets

    Normalized, enriched and linked across the ecosystem.

  3. 03 Data products

    Published in ODPS-family formats with clear structure and reuse potential.

  4. 04 Use cases and graph

    Explicit relationships between use cases, data products, datasets and organizations.

  5. 05 Agent-ready resources

    Files ready for AI agents, APIs and automated workflows.

What can you explore?

Questions the platform can help everyday users, researchers, builders and innovators answer.

01

Which open data portals are most relevant for my topic?

02

Which data products could help me start faster?

03

What use cases already exist in this area?

04

Which places have the strongest data coverage?

05

What ready-to-use data packages can I download?

06

What can I ask the Assistant to help me explore?

A shared Open Data Value Layer

People
Data
Solutions
A more open world

Towards a global open data value layer

Each catalog in this portal is analyzed independently, but transformed into the same interoperable structure. As more catalogs are added, this creates a new way to explore open data across organizations, cities and countries.

The long-term aim is to create a shared, machine-readable view of open data around the world, organized around value rather than portal boundaries.

Which jurisdictions publish data for the same use case?

Which recurring data products appear across countries?

What datasets are commonly required for a particular outcome?

What open data resources could an AI agent use across several jurisdictions?

  1. 01TodayIndividual catalog analyses
  2. 02NextShared structures across catalogs
  3. 03Longer termGlobal Open Data Value Graph

Frequently asked questions

Short answers about what the portfolios show, how they are generated and how another open data portal can be added.

What is an Open Data Value Portfolio?

It is a transformed view of an open data portal that organizes source datasets into data products, use cases, relationships, analysis and AI-agent-ready resources. The portfolio helps people move from a long dataset list to a clearer view of what the published data can enable.

Is this the same as the original open data catalog?

No. The source catalog remains the evidence base and the portfolio is a value-oriented layer built from that evidence. It does not replace the portal; it makes the portal easier to inspect through products, use cases, relationships and machine-readable outputs.

How do we get our open data portal added?

Contact Jarkko Moilanen to discuss adding your open data portal and creating an Open Data Value Portfolio for it. The starting point is usually a short review of your catalog API, metadata quality, languages, branding needs and intended audience.

What source data do you need?

The preferred input is public catalog metadata from a REST API such as Huwise or Opendatasoft. CSV exports can also be used when an API is not available, as long as the metadata describes datasets, publishers, domains, formats, update signals and access links well enough for analysis.

Are the data products official publications?

No. They are generated portfolio outputs for review and validation, based on the public evidence available in the source catalog. They should be treated as analysis outputs until the owning organization reviews, approves or publishes them through its own governance process.

Does each portfolio stay separate?

Yes. Each analyzed portal has its own workspace, route, files and Assistant grounding. Portfolios can be compared later through shared structures, but the source evidence, generated resources and Assistant context remain separated by portal.

Can the Assistant answer questions about every portal?

The Assistant is scoped to the portfolio the visitor is viewing, so answers are grounded in that portal's workspace and generated resources. This keeps answers from mixing Ajman, Bahrain or any other portfolio unless a cross-portfolio view is intentionally created.

Can the output support Arabic?

Yes. The productization plan supports language configuration and Arabic views where the portal package is configured for Arabic. Translation can use an LLM as part of the generation process, while the final wording should still be reviewed by the portfolio owner.

Can we influence the design of a generated portfolio?

Yes. Portal packages can include branding, CSS, language settings, source settings, LLM configuration and other options that affect the generated experience. The goal is for each portfolio to feel connected to its source organization while keeping the Open Data Value structure consistent.

What machine-readable outputs are produced?

The portfolio can expose structured graph, search, dataset, data product and standards-oriented resources so applications and AI agents can consume the outputs directly. These outputs make the portfolio useful beyond the web page, including agent grounding, integration workflows and downstream product development.