Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations

Eisa Alharbi, John Howse, Gem Stapleton, Ali Hamie, Anestis Touloumis

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

Abstract

Our aim is to provide empirical evidence that diagrammatic logics are more effective than symbolic and textual logics in allowing people to better understand information. Ontologies provide an important focus for such an empirical study: people need to understand the axioms of which ontologies comprise. A between-groups study compared six frequently-used axiom types using the (textual) Manchester OWL Syntax (MOS), (symbolic) description logic (DL) and concept diagrams. Concept diagrams yielded significantly better task performance than DL for all six, and MOS for four, axiom types. MOS outperformed concept diagrams for just one axiom type and DL for only three axiom types. Thus diagrams could ensure ontologies are developed more robustly.
Original languageEnglish
Title of host publicationIEEE Symposium on Visual Languages and Human-Centric Computing 2017
Place of PublicationUSA
PublisherIEEE
Pages0-0
Number of pages1
ISBN (Print)9781538604434
Publication statusPublished - 17 Dec 2017
EventIEEE Symposium on Visual Languages and Human-Centric Computing 2017 - Raleigh, North Carolina, USA, 11-14 October 2017
Duration: 13 Nov 2017 → …

Conference

ConferenceIEEE Symposium on Visual Languages and Human-Centric Computing 2017
Period13/11/17 → …

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Ontology

Bibliographical note

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

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Alharbi, E., Howse, J., Stapleton, G., Hamie, A., & Touloumis, A. (2017). Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations. In IEEE Symposium on Visual Languages and Human-Centric Computing 2017 (pp. 0-0). USA: IEEE.
Alharbi, Eisa ; Howse, John ; Stapleton, Gem ; Hamie, Ali ; Touloumis, Anestis. / Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations. IEEE Symposium on Visual Languages and Human-Centric Computing 2017. USA : IEEE, 2017. pp. 0-0
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Alharbi, E, Howse, J, Stapleton, G, Hamie, A & Touloumis, A 2017, Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations. in IEEE Symposium on Visual Languages and Human-Centric Computing 2017. IEEE, USA, pp. 0-0, IEEE Symposium on Visual Languages and Human-Centric Computing 2017, 13/11/17.

Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations. / Alharbi, Eisa; Howse, John; Stapleton, Gem; Hamie, Ali; Touloumis, Anestis.

IEEE Symposium on Visual Languages and Human-Centric Computing 2017. USA : IEEE, 2017. p. 0-0.

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

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Alharbi E, Howse J, Stapleton G, Hamie A, Touloumis A. Visual Logics Help People: An Evaluation of Diagrammatic, Textual and Symbolic Notations. In IEEE Symposium on Visual Languages and Human-Centric Computing 2017. USA: IEEE. 2017. p. 0-0