Information visualization: from petroglyphs to CoDe Graphs

2016 - 2017Data visualization concerns the communication of data through visual representations and techniques. It aims at enhancing perception and support data-driven decision making so enabling insights otherwise hard to achieve. A good visualization of data makes it possible to identify patterns and enables better understanding of phenomena. In other words, data visualization is related to an innate human ability to quickly comprehend, discern and convert patterns into useful and usable information. Humans have used visual graphical representations as early as 35.000 B.C., through cave drawings. Indeed, human ancestors already reasoned in terms of models or schemata: the visual representation of information is an ancient concept, as witnessed by the rock carvings found. Over the centuries, information visualization has evolved to take into account the changing human needs and its use has become more and more conscious. The first data visualization techniques have been developed to observe and represent physical quantities, geography and celestial positions. Successively, the combined use of euclidean geometry and algebra improved accuracy and complexity of information representation, in different fields, such as astronomy, physics and engineering. Finally, in the last century most modern forms of data representations were invented: starting from charts, histograms, and graphs up to high dimensional data, and dynamic and interactive visualizations of temporal data [41]. Nowadays, the huge amount of information enables more precise interpretation of phenomena so fostering the adoption of infographic techniques, in particular, for supporting managerial decision-making in the business area... [edited by author]XVI n.s

Spatio-temporal Reasoning for Vague Regions

Abstract. This paper extends a mereotopological theory of spatiotemporal reasoning to vague ”egg-yolk ” regions. In this extension, the egg and its yolk are allowed to move and change over time. We present a classification of motion classes for vague regions as well as composition tables for reasoning about moving vague regions. We also discuss the formation of scrambled eggs when it becomes impossible to distinguish the yolk from the white and examine how to incorporate temporally and spatially dispersed observations to recover the yolk and white from a scrambled egg. Egg splitting may occur as a result of the recovery process when available information supports multiple egg recovery alternatives. Egg splitting adds another dimension of uncertainty to reasoning with vague regions.