Using Knowledge Graphs for Architecting and Implementing Air Quality Data Exchange: Australian Context

Gill, A; Bandara, M

Using Knowledge Graphs for Architecting and Implementing Air Quality Data Exchange: Australian Context

Gill, A

Bandara, M

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Publisher:: ASSOC COMPUTING MACHINERY
Publication Type:: Conference Proceeding
Citation:: ACM International Conference Proceeding Series, 2024, pp. 534-541
Issue Date:: 2024-06-11

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Field	Value	Language
dc.contributor.author	Gill, A https://orcid.org/0000-0001-6239-6280
dc.contributor.author	Bandara, M
dc.contributor.editor	Liao, HC
dc.contributor.editor	Cid, DD
dc.contributor.editor	Macadar, MA
dc.contributor.editor	Bernardini, F
dc.date	2024-06-11
dc.date.accessioned	2024-11-19T03:28:05Z
dc.date.available	2024-11-19T03:28:05Z
dc.date.issued	2024-06-11
dc.identifier.citation	ACM International Conference Proceeding Series, 2024, pp. 534-541
dc.identifier.uri	http://hdl.handle.net/10453/181980
dc.description.abstract	The air quality data ecosystem consists of several interacting actors such as government agencies and researchers that collect large volumes of data from different air quality monitoring stations via IoT sensors and data systems. The challenge is: how to enable data linking and sharing in the complex and federated data ecosystem for more comprehensive research and reporting for air quality improvement? This paper presents a knowledge graph-based approach for architecting and implementing the air quality data exchange platform for enabling the data linking and sharing in the federated air quality data ecosystem. The application of the proposed approach is demonstrated with the help of an air quality data case study example in the Australian context. This work has been done as a part of the large air quality digital data infrastructure project with the state and local government. The learnings from this paper can be used by government agencies and researchers for architecting and implementing knowledge-graph based data exchanges as appropriate to their context.
dc.language	en
dc.publisher	ASSOC COMPUTING MACHINERY
dc.relation.ispartof	ACM International Conference Proceeding Series
dc.relation.ispartof	25th Annual International Conference on Digital Government Research (DGO) - Internet of Beings - Transforming Public Governance
dc.relation.isbasedon	10.1145/3657054.3657117
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Using Knowledge Graphs for Architecting and Implementing Air Quality Data Exchange: Australian Context
dc.type	Conference Proceeding
utslib.location.activity	TAIWAN, Taipei
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Australian Artificial Intelligence Institute (AAII)
pubs.organisational-group	University of Technology Sydney/UTS Groups/Global Big Data Technologies Centre (GBDTC)
pubs.organisational-group	University of Technology Sydney/UTS Groups/The Trustworthy Digital Society
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2024-11-19T03:28:03Z
pubs.finish-date	2024-06-14
pubs.publication-status	Published
pubs.start-date	2024-06-11

Abstract:

The air quality data ecosystem consists of several interacting actors such as government agencies and researchers that collect large volumes of data from different air quality monitoring stations via IoT sensors and data systems. The challenge is: how to enable data linking and sharing in the complex and federated data ecosystem for more comprehensive research and reporting for air quality improvement? This paper presents a knowledge graph-based approach for architecting and implementing the air quality data exchange platform for enabling the data linking and sharing in the federated air quality data ecosystem. The application of the proposed approach is demonstrated with the help of an air quality data case study example in the Australian context. This work has been done as a part of the large air quality digital data infrastructure project with the state and local government. The learnings from this paper can be used by government agencies and researchers for architecting and implementing knowledge-graph based data exchanges as appropriate to their context.

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http://hdl.handle.net/10453/181980