Getting Formal Ontologies Closer to Final Users Through Knowledge Graph Visualization: Interpretation and Misinterpretation

Pileggi, SF

Getting Formal Ontologies Closer to Final Users Through Knowledge Graph Visualization: Interpretation and Misinterpretation

Pileggi, SF

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Publisher:: Springer International Publishing
Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, 13353 LNCS, pp. 611-622
Issue Date:: 2022-06-21

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Field	Value	Language
dc.contributor.author	Pileggi, SF
dc.date	2022-06-21
dc.date.accessioned	2022-11-01T23:02:04Z
dc.date.available	2022-11-01T23:02:04Z
dc.date.issued	2022-06-21
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2022, 13353 LNCS, pp. 611-622
dc.identifier.isbn	9783031087592
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/163123
dc.description.abstract	Knowledge Graphs are extensively adopted in a variety of disciplines to support knowledge integration, visualization, unification, analysis and sharing at different levels. On the other side, Ontology has gained a significant popularity within machine-processable environments, where it is extensively used to formally define knowledge structures. Additionally, the progressive development of the Semantic Web has further contributed to a consolidation at a conceptual level and to the consequent standardisation of languages as part of the Web technology. This work focuses on customizable visualization/interaction, looking at Knowledge Graphs resulting from formal ontologies. While the proposed approach in itself is considered to be scalable via customization, the current implementation of the research prototype assumes detailed visualizations for relatively small data sets with a progressive detail decreasing when the amount of information increases. Finally, issues related to possible misinterpretations of ontology-based knowledge graphs from a final user perspective are briefly discussed.
dc.language	en
dc.publisher	Springer International Publishing
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartof	International Conference on Computational Science 2022
dc.relation.isbasedon	10.1007/978-3-031-08760-8_50
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Getting Formal Ontologies Closer to Final Users Through Knowledge Graph Visualization: Interpretation and Misinterpretation
dc.type	Conference Proceeding
utslib.citation.volume	13353 LNCS
utslib.location.activity	London
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 - PERSWADE - Centre on Persuasive Systems for Wise Adaptive Living
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	embargoed	*
pubs.consider-herdc	false
utslib.copyright.embargo	2024-06-15T00:00:00+1000Z
dc.date.updated	2022-11-01T23:02:03Z
pubs.finish-date	2022-06-23
pubs.publication-status	Published
pubs.start-date	2022-06-21
pubs.volume	13353 LNCS

Abstract:

Knowledge Graphs are extensively adopted in a variety of disciplines to support knowledge integration, visualization, unification, analysis and sharing at different levels. On the other side, Ontology has gained a significant popularity within machine-processable environments, where it is extensively used to formally define knowledge structures. Additionally, the progressive development of the Semantic Web has further contributed to a consolidation at a conceptual level and to the consequent standardisation of languages as part of the Web technology. This work focuses on customizable visualization/interaction, looking at Knowledge Graphs resulting from formal ontologies. While the proposed approach in itself is considered to be scalable via customization, the current implementation of the research prototype assumes detailed visualizations for relatively small data sets with a progressive detail decreasing when the amount of information increases. Finally, issues related to possible misinterpretations of ontology-based knowledge graphs from a final user perspective are briefly discussed.

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http://hdl.handle.net/10453/163123