Data and information visualization: Difference between revisions

Revision as of 07:26, 31 January 2025

Revision as of 02:26, 9 February 2025

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The [[Congressional Budget Office]] summarized several best practices for graphical displays in a June 2014 presentation. These included: a) Knowing your audience; b) Designing graphics that can stand alone outside the report's context; and c) Designing graphics that communicate the key messages in the report.<ref>{{cite web|url=https://www.cbo.gov/publication/45224|title=Telling Visual Stories About Data - Congressional Budget Office|website=www.cbo.gov|access-date=2014-11-27|archive-url=https://web.archive.org/web/20141204135630/https://www.cbo.gov/publication/45224|archive-date=2014-12-04|url-status=live}}</ref>

Useful criteria for a data or information visualization include:<ref name=IEEExplore_2007>{{cite journalbook |last1=Kosara |first1=Robert |title=2007 11th International Conference Information Visualization (IV '07) |chapter=Visualization Criticism - The Missing Link Between Information Visualization and Art |journal=IEEE Xplore |date=16 July 2007 |pages=631–636 |doi=10.1109/IV.2007.130 |isbn=978-0-7695-2900-4 |issn=1550-6037}} Published in "2007 11th International Conference Information Visualization (IV '07)"</ref>

# It is based on (non-visual) data - that is, a data/info viz is not image processing and collage;'''

# It creates an image - specifically that the image plays the primary role in communicating meaning and is not an illustration accompanying the data in text form; and

# 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 |first1=C. |last2=Kosara |first2=R. |title=Embedding Information Visualization within Visual Representation (chapter in Advances in Information and Intelligent Systems) |journal=Studies in Computational Intelligence |date=2009 |volume=251 |pages=307-326307–326 |doi=10.1007/978-3-642-04141-9_15 |publisher=Springer |___location=Berlin, Heidelberg}}</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).