The Open Geospatial Consortium (OGC) invites public comment on the candidate OGC EmissionML Standard, a proposed framework for standardized, interoperable representation of emission event data across environmental monitoring and reporting systems.

Overview

This OGC Standard defines EmissionML, a conceptual data model for representing emission events. EmissionML provides a domain-specific ontology for describing the release of substances into the atmosphere, including the source from which an emission originates, the mechanism by which it occurs, the quantity of substance released, and the temporal bounds of the event.

Key Principles of EmissionML

EmissionML is designed around three key principles.

First, it incorporates an evidence chain linking emission determinations to supporting Observations, enabling traceability from reported values to the underlying measurements.

Second, it provides explicit uncertainty provenance by attaching data quality metadata to both emission quantities and temporal bounds, ensuring that the confidence and precision of each determination are recorded alongside the reported values.

Third, it provides clear spatial and temporal context. Spatial context is represented through Feature, the ultimate feature of interest, and Source, the origin of the emission. Temporal context is represented through start time, end time, and the phenomenon time of supporting Observations.

Supporting Interoperable Emissions Data

By adopting the OMS 3.0 Observation model, EmissionML provides a common framework for reconciling heterogeneous sensor observations — from remote sensing satellites to ground-based continuous monitoring stations — within a unified evidence chain.

The model builds on foundational OGC and ISO standards. Source inherits from the ISO General Feature Model (ISO 19109), Determination Procedure inherits from Procedure OGC Observations, Measurements, and Samples (OMS 3.0: OGC Abstract Specification Topic 20 – 20-082r4, also ISO/OGC 19156:2023), and Observations conform to the OMS 3.0 Observation model.

The standard defines 12 requirements specifying the structure and constraints of the core data model.

Why EmissionML Matters

By making emission semantics, evidence chains, and uncertainty provenance explicit and machine-verifiable, EmissionML gives both human auditors and AI agents the grounded context required to verify the credibility of reported emission values, trace determinations to their supporting observations and procedures, and reproduce emission assessments across organizations and jurisdictions.

Who Should Comment

The intended audience includes environmental regulators, greenhouse gas reporting frameworks, emissions monitoring system developers, and geospatial data infrastructure implementers requiring a standardized, interoperable representation of emission event data.

How to Comment

The candidate EmissionML Standard is available for review and comment for a period of 30 days. Comments are due by 18 June, 2026.

Comments can be submitted in the OGC GitHub repository for a period ending on the “Close request date” listed above. Comments received will be consolidated and reviewed by OGC members for potential incorporation into the document.

About OGC

The Open Geospatial Consortium (OGC) is a membership organization dedicated to using the power of geography and technology to solve problems faced by people and the planet. OGC unlocks value and opportunity for its members through Standards, Innovation, and Collaboration.

OGC’s membership represents a diverse and active global community drawn from government, industry, academia, international development agencies, research and scientific organizations, civil society, and advocates.

Visit ogc.org for more information about OGC’s work.