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MCDS — MortarCAPS Higher Learning Data Standard

Audiences

Standards as infrastructure.

MCDS gives governments and regulators a sovereign, sector-owned data layer that supports skills policy, AI assessment validation, prior-learning recognition, and reporting — without ceding the substrate to a private vendor.

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01 Where MCDS supports policy

Three policy areas where the standard does the heavy lifting.

Skills & CPL/PLAR

Recognise what people can do.

With MCDS-aligned data — and HCR on top of it — governments can recognise capability acquired through prior learning, on-the-job experience, and informal learning, with a verifiable trail.

AI assessment

Validate the inputs, not just the output.

AI-assessment systems require semantically consistent inputs to be defensible. MCDS gives regulators a way to specify, audit, and validate the data layer underneath any AI assessment claim.

Digital governance

Sovereign by design.

MCDS is governed by sector peak bodies and an independent NFP — not a single vendor. The data substrate of higher learning stays sovereign and sector-owned.

02 Sovereign reporting

One model. Many regulators.

MCDS V2.0.1 ships an XBRL-modelled Reporting Framework with Python validation, and reference data aligned to ABS, ISO, and Statistics Canada — with PESC crosswalk arriving September 2026.

  • AU / NZ

    ABS-aligned, TEQSA-ready reference data.

    Reference datasets are aligned to Australian Bureau of Statistics classifications and ISO standards, simplifying TEQSA, NCVER, and HEIMS-style reporting.

  • Canada

    Statistics Canada classifications shipped.

    From V2.0.1, Canadian institutions can use Statistics Canada classifications natively in MCDS — no cross-mapping required.

  • Cross-border

    PESC crosswalk in September 2026.

    MCDS V2.2 brings formal alignment with the US PESC standard, opening cross-border interoperability for credentials and reporting.

  • Polymorphic by design

    Use the standard or your own.

    Reference data supports both standardised classifications and institution-defined taxonomies side-by-side, so adoption doesn't force a wholesale change at day one.

Discuss MCDS as policy infrastructure.

If you're building skills policy, AI-assessment regulation, or reporting reform — MCDS is the data layer underneath. Let's talk.

Contact us What is MCDS