Abstract

Carbon reduction activities heavily rely on the ability to access, integrate, and reason over diverse emission reduction datasets, which are isolated and fragmented across different organizations. In this paper we present CRA (Carbon Reduction Assessment) Framework, an ontology-based framework for carbon reduction assessment (CRA framework) and associated knowledge graph. This work builds on our preliminary research, and addresses key challenges identified through the proof-of-concept evaluation improved domain coverage, access by non-IT specialists for decision support, and overcoming limited quantity of data sources. We present an elaborate ontology that capture the complexity of the carbon credit ecosystem, and a knowledge graph based on the ontology that interfaced to variety of external data sources, enabling more refined queries and better semantic coverage. We evaluate the CRA framework to assess its ease of use, coverage, consistency, and accuracy, overall providing strong evidence that the CRA framework in this paper offers promising capabilities in data integration, advanced reasoning, and associated decision-making process.

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