Data and information visualization: Difference between revisions

Revision as of 07:15, 31 January 2025

Revision as of 07:25, 31 January 2025

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# The result is readable.

Readability means that it is possible for a viewer to understand the underlying data, such as by making comparisons between proportionally sized visual elements to compare their respective data values; or using a legend to decode a map, like identifying coloured regions on a climate map to read temperature at that ___location. For greatest efficiency and simplicity of design and user experience, this readability is enhanced through the use of bijective mapping in that design of the image elements - where the mapping of representational element to data variable is unique.<ref name=StudiesComputIntell_2009>{{cite journal |last1=Ziemkiewicz, Caroline,|first1=C. |last2=Kosara, Robert (2010)|first2=R. |title=Embedding Information Visualization Withinwithin Visual Representation, (chapter in Ras, Ribarsky, Advances in Information and Intelligent Systems) |journal=Studies in Computational Intelligence |date=2009 |volume=251 |pages=307-326 |doi=10.1007/978-3-642-04141-9_15 |publisher=Springer |___location=Berlin, Heidelbert}}</ref>.

Kosara (2007)<ref name=IEEExplore_2007/> also identifies the need for a visualisation to be "recognisable as a visualisation and not appear to be something else". He also states that recognisability and readability may not always be required in all types of visualisation e.g. "informative art" - (which would still meet all three above criteria but might not look like a visualisation;) or "artistic visualisation" - (which similarly is still based on non-visual data to create an image, but may not be readable or recognisable).

===Quantitative messages===