Visualization of Multiple Ontology Agro Knowledge Mining Model

Abstract

Agriculture is an important sector which contributes to 17% of the total GDP of the Indian economy. Soil, crop type, location and season play a major role in agriculture. Quality seed, water, soil, chemical composition, disease prevention are important parameters in Quality crops. Growth in agriculture and modern techniques has given out a new dimension to modern agriculture processes which differ from traditional agriculture. This in turn reduces the workload of farmers and increases productivity. Experienced farmers have great knowledge about farming techniques, crop selection, disease prevention, soil composition and crop management techniques and their composition. Due to less productivity, water, labor and pest management knowledge transfer is not done to the next generation. This system attempts to provide a visualization of knowledge management systems. Data visualization is one of the modern techniques for data representation. Agriculture yield, crop selection, soil composition can be represented in a visualization technique which will help the farmers for better understanding than representing the data in table or text. In this paper, a visualization of an agro knowledge mining approach which extracts knowledge from multiple ontology is proposed.