TY - GEN
T1 - Modular Graphical Ontology Engineering Evaluated
AU - Shimizu, Cogan
AU - Hammar, Karl
AU - Hitzler, Pascal
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Ontology engineering is traditionally a complex and time-consuming process, requiring an intimate knowledge of description logic and predicting non-local effects of different ontological commitments. Pattern-based modular ontology engineering, coupled with a graphical modeling paradigm, can help make ontology engineering accessible to modellers with limited ontology expertise. We have developed CoModIDE, the Comprehensive Modular Ontology IDE, to develop and explore such a modeling approach. In this paper we present an evaluation of the CoModIDE tool, with a set of 21 subjects carrying out some typical modeling tasks. Our findings indicate that using CoModIDE improves task completion rate and reduces task completion time, compared to using standard Protégé. Further, our subjects report higher System Usability Scale (SUS) evaluation scores for CoModIDE, than for Protégé. The subjects also report certain room for improvements in the CoModIDE tool – notably, these comments all concern comparatively shallow UI bugs or issues, rather than limitations inherent in the proposed modeling method itself. We deduce that our modeling approach is viable, and propose some consequences for ontology engineering tool development.
AB - Ontology engineering is traditionally a complex and time-consuming process, requiring an intimate knowledge of description logic and predicting non-local effects of different ontological commitments. Pattern-based modular ontology engineering, coupled with a graphical modeling paradigm, can help make ontology engineering accessible to modellers with limited ontology expertise. We have developed CoModIDE, the Comprehensive Modular Ontology IDE, to develop and explore such a modeling approach. In this paper we present an evaluation of the CoModIDE tool, with a set of 21 subjects carrying out some typical modeling tasks. Our findings indicate that using CoModIDE improves task completion rate and reduces task completion time, compared to using standard Protégé. Further, our subjects report higher System Usability Scale (SUS) evaluation scores for CoModIDE, than for Protégé. The subjects also report certain room for improvements in the CoModIDE tool – notably, these comments all concern comparatively shallow UI bugs or issues, rather than limitations inherent in the proposed modeling method itself. We deduce that our modeling approach is viable, and propose some consequences for ontology engineering tool development.
UR - http://corescholar.libraries.wright.edu/cse/743
UR - https://www.scopus.com/pages/publications/85086143093
UR - https://www.scopus.com/pages/publications/85086143093#tab=citedBy
U2 - 10.1007/978-3-030-49461-2_2
DO - 10.1007/978-3-030-49461-2_2
M3 - Conference contribution
AN - SCOPUS:85086143093
SN - 9783030494605
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 20
EP - 35
BT - The Semantic Web - 17th International Conference, ESWC 2020, Proceedings
A2 - Harth, Andreas
A2 - Kirrane, Sabrina
A2 - Ngonga Ngomo, Axel-Cyrille
A2 - Paulheim, Heiko
A2 - Rula, Anisa
A2 - Gentile, Anna Lisa
A2 - Haase, Peter
A2 - Cochez, Michael
PB - Springer
T2 - 17th Extended Semantic Web Conference, ESWC 2020
Y2 - 31 May 2020 through 4 June 2020
ER -