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Government of Canada – DTPR AI Register

AI-Assisted Anomaly Detection in Ocean Sensor Data

Ecology · Research & Development

What it collects

About a measurement
Anonymized data
  • Conductivity, temperature, and depth (CTD) readings collected from ocean sensors. These are physical measurements of the marine environment with no personal information attached.
Run by
Fisheries and Oceans Canada (DFO)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Not stated by the Helpful Places.

What it is for

EcologyResearch & Development

This system uses machine learning to automatically detect unusual patterns in conductivity, temperature, and depth (CTD) measurements collected from the ocean. It flags significant physical events in oceanographic data so that scientists can investigate them more closely. The system is used internally by Fisheries and Oceans Canada employees and does not process personal information.

What it collects and what happens to it

Data taken in

About a measurement
Anonymized data
  • Conductivity, temperature, and depth (CTD) readings collected from ocean sensors. These are physical measurements of the marine environment with no personal information attached.

Processing

Anomaly Detection
  • Machine learning models trained to identify unusual patterns or deviations in CTD time-series data, flagging significant physical ocean phenomena for scientific follow-up.

What it does

Deciding (Analytical AI)
Human decides
  • Scores and flags CTD data records that deviate from expected oceanographic baselines, returning anomaly signals for review by scientists. Scientists decide which flagged events to investigate further.

Outputs

About a measurement
Anonymized data
  • Anomaly flags and scores applied to CTD data records, indicating which measurements represent significant deviations from expected oceanographic conditions. No personal information is produced.
A recommendation or prediction
Anonymized data
  • Highlights and prioritizes anomalous CTD records for closer investigation by scientists, effectively recommending which data points warrant further scientific attention.

Run by

Fisheries and Oceans Canada (DFO)
  • Federal department responsible for safeguarding Canada's waters and managing its fisheries and oceans resources. Deploys this system internally for use by its scientists.

Government of Canada AI and Data Use Register — Oceanographic Anomaly Detection

Built by

Government of Canada
  • The system was developed in-house by the Government of Canada, meaning the same sovereign body is both developer and deployer.

Government of Canada AI and Data Use Register — Oceanographic Anomaly Detection

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
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 data
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 data
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

  • Right to Algorithmic TransparencyThis system is publicly disclosed on the Government of Canada AI and Data Use Register. Citizens may consult the register entry for information about the system's purpose and scope. As it operates on non-personal oceanographic data, individual data-subject rights do not apply; however, the Government of Canada's broader open-government commitments support transparency about its AI systems.

Risks and safeguards

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