spinner

Lifecycle Management

Understand the development status, support level and future evolution of Open Data Hub APIs, tools, features and datasets. Our lifecycle model helps developers and organisations choose the right components, plan integrations and prepare for changes.

Why Lifecycle Management

Open Data Hub evolves continuously through research projects, community contributions and production services. Lifecycle Management makes this evolution transparent. Each component and dataset is assigned a clear status, so users can understand its stability, documentation level, support model and expected future.

  • Choose components that match your production and innovation needs.
  • Identify experimental services before building critical integrations.
  • Receive clear notice when a component or dataset is being deprecated.
  • Plan migrations before a scheduled shutdown or removal.
  • Find the official replacement, documentation and related updates.

Technical components lifecycle

Overview of status levels and operational definitions for technical components.

State Public description Operational meaning
R&D / Beta Experimental components being tested and evaluated before a decision is made about production adoption. Changes and downtime may occur; breaking changes are possible; documentation and customer-care knowledge may be limited; the component may be discontinued if it is not used or no longer strategic.
Core / Production Stable components that form part of the Open Data Hub production environment. Actively maintained; documented; known by customer care; stability is prioritised; breaking changes and downtime are avoided and communicated in advance whenever possible.
Deprecated Components that are no longer part of the supported core and are planned for shutdown. No active support or further development; availability is not guaranteed; the standard shutdown target is 12 months after the official announcement unless another date is stated.

Dataset lifecycle

Datasets use the three main lifecycle labels, with an additional Archived badge for historical data. The criteria focus on data reliability, continuity, relevance and intended use.

State Dataset-specific meaning Recommended user guidance
R&D / Beta Research, pilot or newly integrated data. Coverage, schema, update frequency or quality may still change. Suitable for exploration and testing. Do not assume continuity or production-level quality unless explicitly stated.
Core / Production Reliable, relevant datasets with an identified provider, documented access method and maintained ingestion process. Suitable for production use, subject to the licence, access conditions and dataset-specific quality information.
Deprecated Data that is no longer reliable, relevant or maintained, or whose source/project has changed or ended. Do not start new integrations. Existing users should migrate to the indicated replacement before the removal date.
Archived Historical data retained for reference, research or reproducibility, but no longer actively updated. Suitable for historical analysis. Do not expect new records, current coverage or ongoing provider updates.

Deprecation policy

When a component or dataset enters Deprecated status, Open Data Hub publishes an official notice with the reason, affected users, replacement where available and a planned shutdown or removal date. The standard deprecation period is 12 months from the official announcement unless the Open Data Hub core team publishes a different timeframe.

  • Announcements are published on the Updates page and lifecycle directory.
  • High-impact changes are communicated directly to registered users and through the Community Update email.
  • Relevant changes are presented at Open Data Hub events where appropriate.
  • Technical migration instructions belong in the documentation/changelog and are linked from the public notice.
  • A deprecated service retained for a specific customer may require a paid premium service agreement.

FAQ

Question Answer
Can I use an R&D/Beta component in production? You can test it, but availability, interfaces and support may change. Assess the risk and avoid critical dependencies unless agreed with the Open Data Hub team.
How will I know that something is deprecated? The status directory and Updates page show official notices. Registered users may also receive direct email communication for relevant changes.
Is every deprecated item removed after 12 months? Twelve months is the standard target. The official notice is authoritative and may define a different date when necessary.
Where do I find breaking technical changes? Use the technical changelog, filtered by component, endpoint and version.
What happens to deprecated datasets? They remain visible during the migration period with an explanation and removal date. Historical data that remains useful may then be retained with an Archived badge; otherwise the dataset moves to deprecation history.