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

Stefano Germano; Carla Saunders; Ian Horrocks; Rick Lupton

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

Stefano Germano, Carla Saunders, Ian Horrocks, Rick Lupton

Research output: Contribution to journal › Conference article › peer-review

Abstract

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. Here we present a demonstration of the "Physical Resources Observatory" (PRObs) system, which exploits Semantic Web technologies to integrate and reason on top of this diverse production system data. We demonstrate how this system supports domain experts to load datasets, map them to the ontology, and query the extended data to meet several modelling use cases.

Original language	English
Article number	354
Journal	CEUR Workshop Proceedings
Volume	2980
Publication status	Published - 31 Dec 2021
Event	2021 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2021 - Virtual, Online Duration: 24 Oct 2021 → 28 Oct 2021

Keywords

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

ASJC Scopus subject areas

Computer Science(all)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

http://ceur-ws.org/Vol-2980/paper354.pdfLicence: Unspecified

Cite this

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title = "Use of semantic technologies to inform progress toward zero-carbon economy: Extended Abstract",

abstract = "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. Here we present a demonstration of the {"}Physical Resources Observatory{"} (PRObs) system, which exploits Semantic Web technologies to integrate and reason on top of this diverse production system data. We demonstrate how this system supports domain experts to load datasets, map them to the ontology, and query the extended data to meet several modelling use cases.",

keywords = "Data integration, Decision Support System, Material Flow Analysis, Ontology, Resource efficiency, Rule-based approach, Semantic Technology",

author = "Stefano Germano and Carla Saunders and Ian Horrocks and Rick Lupton",

note = "Funding Information: ⋆ This work was supported by the EPSRC project UK FIRES (EP/S019111/1), the SIRIUS Centre for Scalable Data Access (Research Council of Norway), and Samsung Research UK. We would like to acknowledge the support of Jos{\'e} Azevedo and Christopher Cleaver, whose work on the UK production system case study has provided essential context for the development of this work, and the Oxford Semantic Technologies team for their support. Copyright {\textcopyright} 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Publisher Copyright: {\textcopyright} 2021 CEUR-WS. All rights reserved.; 2021 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2021 ; Conference date: 24-10-2021 Through 28-10-2021",

year = "2021",

month = dec,

day = "31",

language = "English",

volume = "2980",

journal = "CEUR Workshop Proceedings",

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T1 - Use of semantic technologies to inform progress toward zero-carbon economy

T2 - 2021 International Semantic Web Conference Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters-Demos-Industry 2021

AU - Germano, Stefano

AU - Saunders, Carla

AU - Horrocks, Ian

AU - Lupton, Rick

N1 - Funding Information: ⋆ This work was supported by the EPSRC project UK FIRES (EP/S019111/1), the SIRIUS Centre for Scalable Data Access (Research Council of Norway), and Samsung Research UK. We would like to acknowledge the support of José Azevedo and Christopher Cleaver, whose work on the UK production system case study has provided essential context for the development of this work, and the Oxford Semantic Technologies team for their support. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). Publisher Copyright: © 2021 CEUR-WS. All rights reserved.

PY - 2021/12/31

Y1 - 2021/12/31

N2 - 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. Here we present a demonstration of the "Physical Resources Observatory" (PRObs) system, which exploits Semantic Web technologies to integrate and reason on top of this diverse production system data. We demonstrate how this system supports domain experts to load datasets, map them to the ontology, and query the extended data to meet several modelling use cases.

AB - 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. Here we present a demonstration of the "Physical Resources Observatory" (PRObs) system, which exploits Semantic Web technologies to integrate and reason on top of this diverse production system data. We demonstrate how this system supports domain experts to load datasets, map them to the ontology, and query the extended data to meet several modelling use cases.

KW - Data integration

KW - Decision Support System

KW - Material Flow Analysis

KW - Ontology

KW - Resource efficiency

KW - Rule-based approach

KW - Semantic Technology

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M3 - Conference article

AN - SCOPUS:85117689104

VL - 2980

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

M1 - 354

Y2 - 24 October 2021 through 28 October 2021

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

UK FIRES: Locating Resource Efficiency at the Heart of Future Industrial Strategy in the UK

Cite this

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

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

Other files and links

Fingerprint

Projects

UK FIRES: Locating Resource Efficiency at the Heart of Future Industrial Strategy in the UK

Cite this