IR frequently generates large volumes of data that require organization, summarizing and visualization so they can be used for various kinds of communication and advocacy, and for different purposes and/or audiences. To help people understand and interpret the significance of specific data it is frequently transformed from raw numbers, to be presented in various visual formats. This often makes previously subtle or invisible patterns, trends or correlations within the data more readily perceived. Like any form of visual presentation, the method you choose to visualize data can emphasize specific characteristics of a given data set, and so care must be taken to choose an objective approach that meets your goal and the needs of a specific audience, and does not affect the integrity of the data itself or present a biased perspective.
A series of examples are provided to illustrate varying data visualization approaches, and the influence this has on how a relatively simple data set is interpreted. Tables 1a to 1b and 2c to 2e present and disaggregate a single set of quantitative data in various ways. Figures 2a to 2c are examples of how the same data can be visualized.