Work

Visual logics help people: An evaluation of diagrammatic, textual and symbolic notations

Year: 2017

Type: conference-paper

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.

Source: IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)

DOI: 10.1109/vlhcc.2017.8103475

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

Institution: University of Brighton

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Leverhulme Trust

Awards: G5227258834, G8526945721