EmissionML is a free and open Open Geospatial Consortium standard ontology and data model for representing and exchanging emission events in a machine-readable, interoperable, and extensible way. It supports multiple emission types, including methane, and aligns with international standards for spatial, temporal, and observational data. EmissionML adheres to the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) to ensure long-term utility across scientific, regulatory, and industrial contexts.
The purpose of the OGC Emission Event Modeling Language (EmissionML) Standard Working Group is to:
- Develop EmissionML, an abstract standard for modeling emission events with interoperability and extensibility in mind.
- Build on the EmissionML model to define a portfolio of open standards for spatiotemporal emission data sharing and analysis.
- Example: MethaneML, a specialized extension of EmissionML for methane emissions and related observational data.
- Publish new OGC Best Practices describing how existing OGC standards can be applied to:
- Estimate the quantity of emission events following existing protocols in accordance with established protocols such as OGMP 2.0, MiQ, and GTI Veritas.
- Determine the occurance and duration of the emission events
EmissionML is built on existing OGC and ISO standards, including:
- ISO/OGC 19156 Observation, Measurement, and Sampling (OMS)
- W3C/OGC Semantic Sensor Networks
- ISO 19157-1:2023 Geographic information — Data Quality
- Unified Code for Units of Measure (UCUM)
- OGC Abstract Specifications
UML diagrams are available in the 25-019 branch.
EmissionML enables:
- Standardized data sharing across emission systems and stakeholders
- Aggregation of emission data from heterogeneous sources
- Reconciliation of emissions with built-in support for:
- Uncertainty modeling
- Machine readability
- Provenance
- Reproducibility
- Explainability
- Georeferencing with explicit location, geometry, and spatial resolution
- Visualization support with native compatibility for GIS overlays and spatial tools
- Flexible reporting formats that support internal analytics and regulatory adaptation
- Built-in provenance for:
- Start and end event determination methods
- Emission quantity estimation method
- Source feature attribution
- Uncertainty modeling following ISO 19157 for:
- Event start and end time
- Quantity of emissions
- Observation results
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Emission Source Operators
Entities responsible for emission-generating facilities or activities. EmissionML enables consistent monitoring, reporting, and compliance workflows. -
Regulators
Authorities and agencies using EmissionML to analyze and verify emissions across geographies and sectors with full transparency and auditability. -
Standards and Certification Bodies
Organizations defining frameworks for GHG measurement and verification. EmissionML provides a consistent, extensible data model for reliable certification. -
Emission Observation Providers
Systems or organizations producing observational or inferred emission data. EmissionML ensures that observational inputs are interoperable with emission records. -
Emergency Responders
Teams responding to accidental or hazardous emission events. EmissionML enhances situational awareness through spatially and temporally accurate event data.
We attened and promoted EmissionML at the following events:
- the 132rd OGC Technical Committee meeting, June 11 2025, Merida, Mexico
- the CSA Scoping Workshop on Evaluating and Selecting Methane Detection, Measurement, and Quantification Technologies, June 20, Calgary, AB, Canada
We will present EmissionML at the following events:
- Expert Group Meeting on Towards A Big Data Revolution for the Planet: From Uncertainty to Opportunity, July 8~10 2025, Frascati, Italy
- The Statistics, Analytics, and GIS for Energy (SAGE) conference, August 13~14, 2025, Des Plaines, IL, USA
- CH4 Connections 2025, October 8~9 2025, Fort Collions, CO, USA
- The 133rd OGC Technical Committee Meeting, Oct 2025, Boulder, CO, USA
For technical discussions, issue tracking, and schema definitions, please refer to the GitHub Issues..
The Part 1 of the EmissionML is in the branch of 25-019.
We hold bi-weekly online meetings to advance the development of the standard and meet in person three times a year at the OGC Technical Committee meetings. If you’re interested in participating, please feel free to contact the SWG Chair, Dr. Steve Liang.
The contributor understands that any accepted contributions may be incorporated into OGC EmissionML standards documents and that all associated copyright and intellectual property rights shall be assigned to the Open Geospatial Consortium (OGC).
The EmissionML Standards Working Group (SWG) at OGC is responsible for the stewardship of the standard. While it maintains formal oversight, the group strives to conduct as much of its work as possible in public.
We welcome Pull Requests from contributors. By submitting a Pull Request or commit to this GitHub repository, you agree to the terms outlined in the Observer Agreement.