BackgroundData is information collected for the purpose of explanation or the result of experimentation or observation. Often we think of data as numbers that represent empirical information but data can be other kinds of information.
Info-graphics or Data visualization is the spatial representations of the data. There are appropriate types of data visualization and inappropriate forms. New Media can create wonderful visualizations by doing transformations on data. However, the user still has to make wise choices. For instance, the computer will rarely make the decisions about the kind of portrayal; those kind of decisions are left to human judgement. Artificial Intelligence (A. I.) hasn't advanced that far yet.
Rules
Consider the information beyond the graphic elements of the chart. A graph needs a context. Without a context a graph is an image that lacks meaning. Below is a list of contextual components that should be considered when creating a graph: Contextual Components
|
PurposeData Visualization is a tool to communicate ideas in a concise easily understand format.
Tufte's PrinciplesGraphic Integrity
Visual representations need to tell the truth. Increase Data-Ink Good graphical representations maximize data-ink and erase4 as much non-data-ink as possible. Avoid Chart-junk Good info-graphics remove unnecessary graphical effects.
Graphing ResourcesHere are links to more information on graphing:
|
References
Tufte, E. R. (1997). Visual explanations. Cheshire, CT: Graphics Press.
Tufte, E. R. (2001). The visual display of quantitative information. (2nd ed.), Cheshire, CT: Graphics Press.
Tufte, E. R. (2001). The visual display of quantitative information. (2nd ed.), Cheshire, CT: Graphics Press.