Effective information visualization is aware of the needs and concerns and the level of expertise of the target audience, deliberately guiding them to the intended conclusion. These verbal and graphical components complement each other to ensure clear, quick and memorable understanding. The visuals are accompanied by supporting texts (labels and titles). Graphical items are well-chosen for the given datasets and aesthetically appealing, with shapes, colors and other visual elements used deliberately in a meaningful and non-distracting manner. The underlying data is accurate and up-to-date to make sure that insights are reliable. Įffective data visualization is properly sourced, contextualized, simple and uncluttered. ( presentational and exploratory visualization) which is different from the field of scientific visualization, where the goal is to render realistic images based on physical and spatial scientific data to confirm or reject hypotheses ( confirmatory visualization). In data and information visualization, the goal is to graphically present and explore abstract, non-physical and non-spatial data collected from databases, information systems, file systems, documents, business and financial data, etc. Visual tools used in information visualization include maps (such as tree maps), animations, infographics, Sankey diagrams, flow charts, network diagrams, semantic networks, entity-relationship diagrams, venn diagrams, timelines, mind maps, etc.Įmerging technologies like virtual, augmented and mixed reality have the potential to make information visualization more immersive, intuitive, interactive and easily manipulable and thus enhance the user's visual perception and cognition. verbal or graphical) and primarily abstract information and its goal is to add value to raw data, improve the viewers' comprehension, reinforce their cognition and help them derive insights and make decisions as they navigate and interact with the computer-supported graphical display. Information visualization, on the other hand, deals with multiple, large-scale and complicated datasets which contain quantitative (numerical) data as well as qualitative (non-numerical, i.e. scatter plots, distribution plots, box-and-whisker plots), geospatial maps (such as proportional symbol maps, choropleth maps, isopleth maps and heat maps), figures, correlation matrices, percentage gauges, etc., which sometimes can be combined in a dashboard. pie charts, bar charts, line charts, area charts, cone charts, pyramid charts, donut charts, histograms, spectrograms, cohort charts, waterfall charts, funnel charts, bullet graphs, etc.), diagrams, plots (e.g. The visual formats used in data visualization include tables, charts and graphs (e.g. When intended for the general public ( mass communication) to convey a concise version of known, specific information in a clear and engaging manner ( presentational or explanatory visualization), it is typically called information graphics.ĭata visualization is concerned with visually presenting sets of primarily quantitative raw data in a schematic form. Typically based on data and information collected from a certain domain of expertise, these visualizations are intended for a broader audience to help them visually explore and discover, quickly understand, interpret and gain important insights into otherwise difficult-to-identify structures, relationships, correlations, local and global patterns, trends, variations, constancy, clusters, outliers and unusual groupings within data ( exploratory visualization). Part of a series on Statisticsĭata and information visualization ( data viz/vis or info viz/vis) is the practice of designing and creating easy-to-communicate and easy-to-understand graphic or visual representations of a large amount of complex quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. Statistician professor Edward Tufte described Charles Joseph Minard's 1869 graphic of Napoleonic France's invasion of Russia as what "may well be the best statistical graphic ever drawn", noting that it captures six variables in two dimensions. It has been merged from Information visualization.
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