Use of semantic technologies to inform progress toward zero-carbon economy

Conference item

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.

Authors: Germano, S; Saunders, C; Horrocks, I; Lupton, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Springer
• Host title: The Semantic Web – ISWC 2021
• Pages: 665-681
• Series: Lecture Notes in Computer Science
• Series number: 12922
• Publication date: 2021-09-30
• Acceptance date: 2021-06-23
• Event title: 20th International Semantic Web Conference (ISWC 2021)
• Event location: Virtual event.
• Event website: https://iswc2021.semanticweb.org/
• Event start date: 2021-10-24
• Event end date: 2021-10-28
• DOI: 10.1007/978-3-030-88361-4_39
• EISBN: 978-3-030-88361-4
• ISBN: 978-3-030-88360-7
• Language: English
• Keywords: material flow analysis; FFR; data integration; ontology; decision support system; resource efficiency; rule-based approach; semantic technology