AI-Assisted Semantic Ontology Creation for Public Service

Research & Development

What it collects

Not stated by the Helpful Places.

Run by: Canada School of Public Service (CSPS)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Not stated by the Helpful Places.

What it is for

Obsidian is an AI system used by the Canada School of Public Service to create semantic web ontologies — structured knowledge representations that define concepts and their relationships. The system is vendor-developed and supports knowledge organization and data interoperability within the public service. Citizens are not directly affected by this system; it is an internal tool for knowledge engineering tasks.

What it collects and what happens to it

Data taken in

Not stated by the Helpful Places.

Processing

Not stated by the Helpful Places.

What it does

Understanding (Semantic AI)

Human decides

The system applies semantic understanding to identify, relate, and structure concepts into a formal ontology. Human knowledge engineers review and approve the resulting ontological structures.

Canada AI Register — Obsidian

Creating (Generative AI)

Human decides

The system generates ontology structure — classes, properties, and relationships — as new structured content that did not previously exist in formal form. Human experts validate all generated ontological artifacts before use.

Canada AI Register — Obsidian

Outputs

Not stated by the Helpful Places.

Run by

Canada School of Public Service (CSPS)

The Canada School of Public Service is the deploying department responsible for this AI system.

Canada AI Register — Obsidian

Built by

Obsidian

Obsidian is the vendor that developed and supplies this AI system for semantic web ontology creation.

Canada AI Register — Obsidian

Kept for

Not stated by the Helpful Places.

Shared with

Not stated by the Helpful Places.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized: Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous: Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable: The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides: This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes: This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous: This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

The Helpful Places has not listed specific rights for this system.

Risks and safeguards

No risks or safeguards have been published for this system yet.