International Journal of Electrical and Computer Engineering (IJECE) Vol. 12, No. 2, April 2022, pp. 1818~1830 ISSN: 2088-8708, DOI: 10.11591/ijece.v12i2.pp1818-1830  1818 Journal homepage: http://ijece.iaescore.com Ontology specific visual canvas generation to facilitate sense-making-an algorithmic approach Kaneeka Vidanage, Noor Maizura Mohamad Noor, Rosmayati Mohemad, Zuriana Abu Bakar Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu, Terengganu, Malaysia Article Info ABSTRACT Article history: Received Mar 22, 2021 Revised Aug 6, 2021 Accepted Sep 1, 2021 Ontologies are domain-specific conceptualizations that are both human and machine-readable. Due to this remarkable attribute of ontologies, its applications are not limited to computing domains. Banking, medicine, agriculture, and law are a few of the non-computing domains, where ontologies are being used very effectively. When creating ontologies for non-computing domains, involvement of the non-computing domain specialists like bankers, lawyers, farmers become very vital. Hence, they are not semantic specialists, particularly designed visualization assistance is required for the ontology schema verifications and sense-making. Existing visualization methods are not fine-tuned for non-technical domain specialists and there are lots of complexities. In this research, a novel algorithm capable of generating domain specialists’ friendlier visualization canvas has been explored. This proposed algorithm and the visualization canvas has been tested for three different domains and overall success of 85% has been yielded. Keywords: Domain-specialist Ontologist Sensemaking Visualization canvas This is an open access article under the CC BY-SA license. Corresponding Author: Noor Maizura Mohamad Noor Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu 21030 Kuala Nerus, Terengganu, Malaysia Email: maizura@umt.edu.my 1. INTRODUCTION In the realm of ontological sensemaking, “visual compactness” is a major bottleneck and an unsolvable issue [1]. For the verification of the suggested conceptualizations, visualization is a must. The screen size, on the other hand, serves as a permanent barrier, limiting understanding of visualized contents for both ontologists and domain experts [2]. Ontology development is a collaborative effort including ontologists and domain experts. Domain specialists are often non-technical individuals such as farmers, attorneys, and medical professionals [3]. However, their participation is critical for the verification of the correctness of the ontology incrementally created by ontologists based on domain expert ’s expert inputs provided [4]. Many current visualization tools are designed with ontologists’ task roles in mind. They are not fine-tuned to conform to the technical challenges that domain experts encounter [5]. However, it is well acknowledged that the logical use of appropriate technology can improve visualization clarity [6]. Consequently, the emphasis of this research is on developing a new algorithm capable of producing more user-friendly visualization canvases for domain experts in an ontology increment-specific manner, with no need for human configuration.