Ontological plant data visualisation using network graphs / Afrina Adlyna Mohamad Matrol - Afrina Adlyna, Mohamad Matrol (2019)
Plant data is heterogeneous, containing complex pictures and consisting of many terminologies that describe plants typically in textual and image forms. The advancement in information technology has led to the development of online database systems, through which the plant data can be shared; accessed and related information to the users’ query be retrieved. However, the retrieved plant data are often presented in lengthy textual and table forms. Consequently, there is inefficiency in elucidating the relationships between plant data in which obtaining new insight from the presented data can be difficult to the users. It should be emphasized that underlining the relationships between data are very important for knowledge enrichment. For the present study, a visual-based representation is proposed to display data to the users in a meaningful way, as it emphasizes the relationships between the data. It involves two main development components; the developments of ontology-driven plant database and plant data visualisation system. Ontological data for plants and samples of trees and shrubs are used as the dataset to be integrated into the proposed plant data visualisation system. The efficiency of the developed visualisation system is measured by performing three types of user evaluation; the usability of heuristic, query and visualisation evaluations, done by the expert and novice users. An ontology-driven plant database named Plant Ontology Universiti Malaya (POUM) and a visualisation system named PlantViz are then developed. POUM consists of plant data and images of 222 plant samples from 43 species of 42 genus for trees and 31 species of 28 genus for shrubs collected around the University of Malaya. PlantViz provides a graphical user interface for users to query the POUM and a graphical viewer to display the results of the query in a form of network graph. The relationships between the data are shown in visualisation form so that users can infer the knowledge and correlate between the data easily. The results from the user evaluation show that the proposed visualisation system is suitable for both users, with or without computer skills. This technique demonstrated the practicability of using computer-assisted tool by providing cognitive analysis in understanding the relationships between data.