Use of Semantic Technologies to Inform Progress Toward Zero-Carbon Economy

Stefano Germano, Carla Saunders, Ian Horrocks, Rick Lupton

Research output: Contribution to journalConference articlepeer-review

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To investigate the effect of possible changes to decarbonise the economy, a detailed picture of the current production system is needed. Material/energy flow analysis (MEFA) allows for building such a model. There are, however, prohibitive barriers to the integration and use of the diverse datasets necessary for a system-wide yet technically-detailed MEFA study. Herein we describe a methodology exploiting Semantic Web technologies to integrate and reason on top of this diverse production system data. We designed an ontology to model the structure of our data, and developed a declarative logic-based approach to address the many challenges arising from data integration and usage in this context. Further, this system is designed for easy access to the needed data in terms relevant for additional modelling and to be applied by non-experts, allowing for a wide use of our methodology. Our experiments with UK production data confirm the usefulness of this methodology through a case study based on the UK production system.
Original languageEnglish
Pages (from-to)665-681
Number of pages17
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Early online date30 Sept 2021
Publication statusPublished - 31 Dec 2021


  • Data integration
  • Decision Support System
  • Material Flow Analysis
  • Ontology
  • Resource efficiency
  • Rule-based approach
  • Semantic technology

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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