Description
Since 2021 the Standards Working Group (Standards WG) of Hyperledger's Climate Action and Accounting Special Interest Group (CA2-SIG) worked on developing an ontology for anthropogenic impact accounting, of which climate accounting is currently the primary use case. The ontology aims to enable interoperability between the plethora of impact accounting standards and methodologies in the market, allowing the further development of systems such as a global climate impact accounting ledger.
Up to date the WG has formulated an ontology comprising a current total of 46 classes and 11 primary axioms with several more axioms on the secondary and tertiary level. The core concepts are explicated on the Standards WG's wiki and encoded in an OWL file. During the 2022/2023 southern hemisphere's summer break the Nova Institute sponsored and hosted a mentorship programme that recruited three second-year ICT university students from South Africa to refine the OWL file, develop a Turtle parser and set up an MVP triple store for the ontology.
The next steps towards operationalization of the ontology are aimed at developing the tools for interoperability between the ontology and existing vocabularies in the field of impact accounting, starting with those from the climate accounting space. This will involve mapping the existing vocabularies and standards to the ontology, improving on the examples produced by the students; annotating existing climate impact data from selected case studies; and building a shape graph to validate annotated data.
Additional Information
Hyperledger Climate Action and Accounting SIG (CA2-SIG)
The core problem being addressed by the ontology
The Anthropogenic Impact Accounting Ontology (AIAO)
A protobuf implementation of the ontology (work in progress)
Learning Objectives
- Develop a deeper understanding of the practical complexities of climate impact accounting, and anthropogenic impact accounting in general.
- Develop a deeper understanding of ontologies, as used in the semantic web, and specifically the AIA ontology.
- Gain practical knowledge of SSSOM, SHACL and either SPARQL or AI algorithms for semantic data processing (the latter depending on the mentee's skillset and interest).