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Capability 2.3.1.1

Standards & Provenance

Definition

Development and enforcement by government or the private sector of interoperable data and metadata standards, quality frameworks and provenance systems that ensure datasets are accurate, traceable and validated throughout their lifecycle.

Examples

  • The Australian Government Data Catalogue
  • ABS Data Quality Framework
  • Australian Government Architecture (AGA)
  • ABS Data Quality Framework (DQF)
  • Data Catalogue Vocabulary – Application Profile for Australia (DCAT-AP-AU).

Indicators

  • Percentage of Commonwealth and state datasets registered in the Australian Government Data Catalogue with complete metadata fields
  • Adoption rate of ABS Data Quality Framework across agencies
  • Existence and currency of agency-specific data standards aligned with AGA

National AI Plan

PLAN COMMITMENT

Limited commitment

Recognises the value of Australian datasets, their importance to developing and training AI models that are locally relevant, and commits to exploring opportunities and pilot use cases to unlock high value datasets, including to build on existing programs of work to improve APS data and data maturity, consistent data standards and metadata, build trusted and secure approaches to data sharing, and identify high value, non-sensitive datasets (Action 2). Refers to verification standards for earth observation data (Action 6), includes updates to privacy laws as part of AI harms mitigation (Action 7), and responsible AI practices in the APS, including documentation, metadata recording and transparency measures (Action 8), but does not include details on implementation or funding, therefore, commitment is assessed to be limited. Limited commitment by government in the plan represents a missed opportunity. More should be done build agency and leverage to offset capability gaps elsewhere in the ecosystem.

Stocktake

Is the Stocktake missing evidence?

Share additional information for potential future Assessments