Smart Mapping Drawing Style for Ordinal Data

Idea created by drcaldwell on Nov 14, 2017
    Reviewed
    Score10
    • drcaldwell

    Request that Esri develop a drawing style for ordinal data, where the categories have a natural order, but distances between categories are not known. Examples would be "Low, Medium High," "Strongly Dislike, Dislike, Neutral, Like, Strongly Like" or "High School, Undergraduate, Masters, PhD" or something similar. 

     

    Current drawing styles accommodate categorical data, but not ordered categorical data. It is time consuming and somewhat complex to symbolize ordinal data by adjusting the individual symbols one by one ("Types (Unique symbols)") or by assigning ordinal categories numbers and then manually classifying these values using ("Counts and Amounts (either Size or Color") and adjusting the labels to match the ordinal categories.

     

    Drawing styles for ordinal data would include a combination of diverging symbols for ordinal categories like  "Strongly Dislike, Dislike, Neutral, Like, Strongly Like" and non-diverging symbols for ordinal categories like "Low, Medium High.

     

    A possible version of the tool would provide the ordered symbols and allow the user to reorder the category values so they would match the symbols, i.e., the application would not necessarily know the order by reading the contents of the variables, but would provide the symbols and let the user adjust the variables and their labels so they match. (It might be possible to encode some common ordinal categories.) As an example, the software would allow the user to select a pattern with five symbols for "Strongly Dislike, Dislike, Neutral, Like, Strongly Like." The symbols would be ordered. The user could then drag a terms, like "Dislike," to match the second symbol in the ordering. 

     

    Symbolizing ordinal data is different than unordered categorical or numerical data, but represents an important type of data for analysts. Developing a Smart Mapping drawing style for ordinal data would address the current gap in drawing styles.