The comprehensibility assessment of visualization of semantic data representation (VSDR) reflecting user capability of knowledge exploration and discovery

• Main Authors: Natanun Kanjanakuha, Paul Janecek, Churee Techawut
• Format: Conference Proceeding
• Published: 2020
• Subjects: Computer Science
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073205845&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/67722
• Institution: Chiang Mai University

© 2019 Association for Computing Machinery. The visual representations of search result querying from encyclopedia by semantic searching tools are rarely found on the internet. Most of the available tools require SPARQL to make some specific queries which are difficult to use, and the visual representation of results on a screen is too complicated to comprehend. The necessity of reducing the complexity of visual structure, supporting user interaction, and increasing the perception of knowledge discovery is considerable. The framework of Visualization of Semantic Data Representation (VSDR) is designed by using the 3-layer approach based on the hyperbolic tree model for visual representation of results from the encyclopedia. The architecture of the searching tool is also designed for novice users. This study presents the result of VSDR usage to the extent of the VSDR's capabilities in terms of comprehensibility, and how the user can perceive a VSDR structure with discoverable knowledge. The result shows that VSDR is an effective searching tool for knowledge exploration and discovery. It has a recognition support reflected in users' perception. It also helped users find answers, learn and gain new knowledge through the representation.