The terms data visualization (or DataViz) and information visualization (or InfoViz) are sometimes used interchangeably. What are the differences between the two terms? This is an old question; however, the unclear definitions and the differences between the two also carry the potential for confusion and misunderstanding.
In computer science, the terms data visualization and information visualization are quite clearly separated. In short, data is actually everything can be stored in bits and bytes. Data visualization are simply all possible forms and techniques of generating images (and moving images) of data.
Depending on the nature of the visualized data and the sectors the data obtained from, the working field of data visualization can be different. For example, spatial data needs geo-visualization and medical records require medical data visualizations (e.g. MRI data).
The field of information visualization is in this context; it is the portion of data visualization, which deals with more abstract.
In order to distinguish information and data visualizations, first you look at the difference of the individual terms of information and data. The BusinessDictionary defines “data” and “information” as:
- Data – Information in raw or unorganized form (such as alphabets, numbers, or symbols) that refers to, or represent, conditions, ideas, or objects. Data is limitless and present everywhere in the universe.
- Information – Data that is accurate and timely, specific and organized for a purpose, presented within a context that gives it meaning and relevance, and can lead to an increase in understanding and decrease in uncertainty.
From these definitions, we can now derive the following difference:
- Data visualizations are those visualizations that may present a (large) data set, but the viewer reveals little or no relevant information.
- Information visualization is a special case of data visualization, in which it is possible to make relevant information visible to the viewer.
Of course, this definition is very subjective. Viewer may have different perspective on what “relevant information” is. Therefore, distinction needs to be recognized in the design process. We end up with the important question of intention, which is behind visualization. For example, when artistic design aspects are in the run in the foreground, probably comes out data visualization; whereas it is about gaining insights into complex issues in the foreground, we end up closer to the information visualizations.
We would then be in the following schematic classification of terms between the poles of art (DataViz) and journalism (InfoViz).
Other opinions on the differences from Quora:
“…it obviously depends on how you define the difference between data, information and knowledge. to me, data visualizations are visualizations that directly plug into data sets to visualize something.”
“…data visualization usually involves the ‘direct’ representation of raw data, information visualization represents data that has been previously processed. Nevertheless, there aren’t much cases where you don’t process your data in any way, so most of the times datavis is equal to infovis.”
“…To me, data visualizations are generally developed around the raw data. Information visualization generally has had some analysis done on the data first (ie. that resulting knowledge is information).”