Ordered small multiple treemaps for visualizing time-varying hierarchical pesticide residue data

摘要: Small multiples can visually enforce comparisons of changes or differences among objects, revealing potential patterns by providing different views. According to the analyzing requirements in food safety fields and characteristics pesticide residue detection data, this paper, we propose a novel visualization approach explore analyze time-varying hierarchical which is called ordered small multiple treemaps (OSMT). Inspired thought querying an array rows columns, OSMT makes it possible locate specific node treemap layout using unique location 2-tuple keep relative stable order nodes while detecting temporal patterns. This algorithm enables visual representation values varying with time, preserving relationships meanwhile. Based on some interaction techniques (filtering, selecting, highlighting zooming, etc.), help users find more easily thus make corresponding decisions efficiency. Besides, also new metric TVA (Ability tracking data treemap) purpose evaluating kinds algorithms from aspect difficulty level for overall layout. Finally, our technique's applicability demonstrated residues results dataset study.