Details
| Original language | English |
|---|---|
| Title of host publication | WWW `24 |
| Subtitle of host publication | Proceedings of the ACM Web Conference 2024 |
| Pages | 4295-4303 |
| Number of pages | 9 |
| ISBN (electronic) | 9798400701719 |
| Publication status | Published - 13 May 2024 |
| Event | 33rd ACM Web Conference, WWW 2024 - Singapore, Singapore Duration: 13 May 2024 → 17 May 2024 |
Abstract
User studies show the demand for diagrammatic reasoning techniques for knowledge representation formats. OWL ontologies are highly relevant for Web 3.0, however, existing ontology visualization tools do not support diagrammatic reasoning, while existing diagrammatic reasoning systems utilize suboptimal visual languages. The purpose of this research is to facilitate the usage of OWL ontologies by providing a diagrammatic reasoning system over their visual representations. We focus on the ALC description logic, which covers most of the expressivity of the ontologies. As a visual language to reason about, we utilize Logic Graphs, which provide the simplest visualizations regarding graph- and information-theoretic properties. We adapt the tableau algorithm to LGs to reason about concept satisfiability, prove the correctness of the proposed system and illustrate it with examples. The proposed diagrammatic reasoning system allows reasoning over ontologies, reducing complex concepts step by step, and identifying elements that produce a contradiction.
Keywords
- description logic, diagrammatic reasoning, logic graphs, ontology visualization, tableau algorithm
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Software
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WWW `24 : Proceedings of the ACM Web Conference 2024. 2024. p. 4295-4303.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Diagrammatic Reasoning for ALC Visualization with Logic Graphs
AU - Baimuratov, Ildar
N1 - Publisher Copyright: © 2024 Owner/Author.
PY - 2024/5/13
Y1 - 2024/5/13
N2 - User studies show the demand for diagrammatic reasoning techniques for knowledge representation formats. OWL ontologies are highly relevant for Web 3.0, however, existing ontology visualization tools do not support diagrammatic reasoning, while existing diagrammatic reasoning systems utilize suboptimal visual languages. The purpose of this research is to facilitate the usage of OWL ontologies by providing a diagrammatic reasoning system over their visual representations. We focus on the ALC description logic, which covers most of the expressivity of the ontologies. As a visual language to reason about, we utilize Logic Graphs, which provide the simplest visualizations regarding graph- and information-theoretic properties. We adapt the tableau algorithm to LGs to reason about concept satisfiability, prove the correctness of the proposed system and illustrate it with examples. The proposed diagrammatic reasoning system allows reasoning over ontologies, reducing complex concepts step by step, and identifying elements that produce a contradiction.
AB - User studies show the demand for diagrammatic reasoning techniques for knowledge representation formats. OWL ontologies are highly relevant for Web 3.0, however, existing ontology visualization tools do not support diagrammatic reasoning, while existing diagrammatic reasoning systems utilize suboptimal visual languages. The purpose of this research is to facilitate the usage of OWL ontologies by providing a diagrammatic reasoning system over their visual representations. We focus on the ALC description logic, which covers most of the expressivity of the ontologies. As a visual language to reason about, we utilize Logic Graphs, which provide the simplest visualizations regarding graph- and information-theoretic properties. We adapt the tableau algorithm to LGs to reason about concept satisfiability, prove the correctness of the proposed system and illustrate it with examples. The proposed diagrammatic reasoning system allows reasoning over ontologies, reducing complex concepts step by step, and identifying elements that produce a contradiction.
KW - description logic
KW - diagrammatic reasoning
KW - logic graphs
KW - ontology visualization
KW - tableau algorithm
UR - http://www.scopus.com/inward/record.url?scp=85194087093&partnerID=8YFLogxK
U2 - 10.1145/3589334.3645607
DO - 10.1145/3589334.3645607
M3 - Conference contribution
AN - SCOPUS:85194087093
SP - 4295
EP - 4303
BT - WWW `24
T2 - 33rd ACM Web Conference, WWW 2024
Y2 - 13 May 2024 through 17 May 2024
ER -