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The growing need to convert the data in databases into knowledge for a public without data visualization expertise requires the ever more precise selection of graphics to be presented to the user for consideration. This can be achieved through a more detailed characterization of the data as well as the data visualization task that the user wishes to accomplish. One way to limit the number of possible graphics based on the data is to characterize the multiple properties that can be described for each variable represented by a column of data. This paper presents seven dimensions with their respective levels that can serve as a framework for classifying statistical graphics such that their effectiveness in performing a given task may then be evaluated.

A Strategy for Automating the Presentation of Statistical Graphics for Users without Data Visualization Expertise - A Position Paper