Abstract—This paper intends to design and simulate a broad knowledge-driven Decision Support Tool (DST) for the floral diversity domain by applying semantic network modelling theory. It emphasizes on how an applied discipline of Information Systems and Technologies uses knowledge gathered over hundreds of years by the scientists and researchers of Bio-diversity domain to arrive at a broad knowledge-driven DST. It introduces the theory of semantic network, concept map modelling and the method of building knowledge-based repository from the vast expanse of research, study and publication knowledge to arrive at a framework for knowledge-driven DST. The said modelling is explained in the light of floral diversity. The system architecture is described with the design aspects of knowledge-driven DST in line with generic operations that can be performed with it. The paper throws light on pros and cons of the designed model. It concludes with the implementation details to show how the field of computerized DST is expanding by using emerging technologies and to create new application for Bio-diversity discipline.

Index Terms—concept map, DST, floral diversity, knowledge-driven tool, semantic network

Cite: Sudhansu Sekhar Dash, Mina Desai, Arghya Ghosh, and Samaresh Das, "Semantic Network Based Modelling to Design a Knowledge-Driven Decision Support Tool for Floral Diversity," Journal of Medical and Bioengineering, Vol. 5, No. 1, pp. 53-57, February 2016. Doi: 10.12720/jomb.5.1.53-57