About Us

Mission

We attempt to break the concept of climate action and the process of climate accounting down to their most essential structures and use that as a basis for designing representation thereof in software.

Our Work

Ontology for Anthropogenic Impact Accounting, AIAO, is a tool for aggregating and consolidating impact accounting data across different standards and vocabularies. The ontology intends to be generic enough for anthropogenic impact accounting in almost any discipline and context, including climate action impact accounting. 

Why it matters

Standardising the semantics of impact data is a prerequisite for trustworthy, decentralised infrastructure. Without a shared vocabulary, ledgers, analytics and audit tools cannot reason over data in a comparable way. With the AIAO suite:

• platforms can exchange and merge impact data

• impact evidence can be verified across platforms

• auditors can follow semantically explicit links from claims to evidence

• developers can reuse common classes and properties instead of inventing new ones

• communities can map legacy schemas into a common model rather than replacing them

History

The Climate Action and Accounting Special Interest Group (CA2-SIG), originally launched under Hyperledger and now part of Linux Foundation Decentralized Trust (LFDT), was formed in 2021 as an open forum comprising domain experts, implementers, and researchers. Their objective was to leverage blockchain and other distributed ledger technologies to advance climate action, enhance transparency in carbon accounting, and support sustainable practices across industries.

Soon a Standards Working Group (WG) was established within the CA2-SIG. Our mission was to distill an architecture-neutral, common language for impact accounting, of which climate accounting was one specific use case.

We quickly realized that the key to developing a vocabulary that can serve such a broad industry and withstand the test of time is to root the vocabulary in a proper ontology. A simple premise anchored the design: "An agent engages in an activity that impacts an environment." From this triad (agent - activity - environment) we built up the ontology and added roles, parameters, instruments, and indicators, as well as the semantics of claims, attestations, and communication.

During the 2022–2023 Southern Hemisphere summer, three South African ICT students contributed to the development process under guidance from SIG members. The students helped convert diagrams to OWL, authored Turtle examples, and prototyped a triple-store for testing. This combination of rigor and practical experimentation laid the foundations for a model that was both conceptually coherent and implementation ready.

By late 2024, the group had a working ontology with dozens of classes and a set of core axioms that captured fundamental concepts of impact accounting.

The first version of the suite was finally released on September 16, 2025, and is now publicly available on W3ID.

How we work

During our biweekly working sessions, our working group iterated from whiteboard models to formal OWL/RDF representations, testing against use cases from carbon accounting, environmental registries, and ESG reporting.

The team validated the framework by mapping sample datasets from well-known programs (e.g., Gold Standard and CDM) to the ontology's concepts, and by tracing end-to-end scenarios from project activity to reported impact and independent attestation.

At the time, however, all the classes and axioms were still part of one, large ontology. This made the ontology difficult for users to grasp and navigate. The WG consequently decided to split the ontology up into a set of smaller ontologies according to the principle of separation of concerns. That effort eventually produced the Anthropogenic Impact Accounting Ontology (AIAO) and three companion ontologies: the Claim Ontology, the Impact Ontology, and the Information Communication Ontology.

All four ontologies are open source (Apache-2.0) and designed to be reused, extended, and mapped to existing standards. Together they provide a framework for describing who did what, with what consequence, how it was evidenced, and how those assertions can be verified and communicated. The framework's vocabulary was carefully chosen to be both human friendly and machine readable.

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