FOI-O: An NZ-first ontology and verification methods package for Freedom of Information process modelling
2026-07-03 • Computation and Language
Computation and Language
AI summaryⓘ
The authors created FOI-O, a method to organize and analyze information request records from public officials, focusing on requests made under New Zealand's Official Information Act. Their system models these records using various data formats and vocabularies to clearly show what happened during the request process without making legal decisions. FOI-O includes tools and examples to help others use and review these workflows, but does not replace human review or provide official legal outcomes. The authors discuss how they built and tested this system and note that it is not legal advice or an official government tool.
Freedom of InformationProcess ModelingOntologyJSON SchemaSKOSOWLRDFSHACLBPMNPetri Net
Authors
Dylan A Mordaunt
Abstract
Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet they also mix observed correspondence, platform states, inferred events, and legal outcomes. FOI-O is a reusable process-modelling method and verification infrastructure for Freedom of Information administration. FOI-O NZ, based on the New Zealand Official Information Act, is the only implemented and validated jurisdictional profile in the current repository. Broader reuse is a design intent and future validation path, not an empirical result of this package. FOI-O models the request record first. Request profiles, observed correspondence events, controlled vocabularies, and provenance make visible what was seen and how it was changed. It then adds review queues, release metadata, bounded agent contracts, semantic assets, process-model artefacts, and fixture-only process-mining interchange examples. Human certification of legally meaningful outcomes stays outside autonomous tooling. The repository provides JavaScript Object Notation (JSON) Schema contracts, Python data models, Simple Knowledge Organization System (SKOS) vocabularies, Web Ontology Language (OWL), Resource Description Framework (RDF), and Shapes Constraint Language (SHACL) assets. These are supported by deterministic examples, release metadata, quality gates, tests, Business Process Model and Notation (BPMN) and Petri Net Markup Language (PNML) process models, XES and OCEL-style fixture exports, and a planned New Zealand annotation task-set manifest. This article describes the motivation, architecture, ontology-development method, validation evidence, and implementation boundaries. The project is not legal advice, is not an official government publication, and does not certify release, refusal, redaction, charging, extension, transfer, complaint, or publication outcomes.