Human-Centered Visualization Environments pp 163-230
Visualization can help in the process of extracting insight from data during decision-making. Its advantages are based on the ability to rapidly interpret large quantities of data. The challenge in this context consists in constructing visualization systems which enable the user to understand and perceive the data effectively by providing transparent interaction methods for effective communication between the user and the data. Ware  states a number of advantages of visualization, namely:
The ability to comprehend huge amounts of data.
The perception of properties that are otherwise not anticipated.
The extraction of problems with data itself, i.e., detecting outliers or anomalies.
The understanding of both large-scale as well as small-scale features of data.
The creation of various hypotheses related to the data.
Information recording, that is related to the usage of visual presentations as a storage mechanism in order to avoid the need for memorization of data and their relationships.
Information communication, where visual representations play the role of a message for communicating the essential features of the data visualized.
Information processing, where visual representations are used as a means to derive knowledge from data.
This chapter is concerned with visual representations in the context of human-centered visualization environments. Considering the variety of issues that relate to visual representations, it will focus on computer-generated visual representations in different contexts. Before introducing the various techniques which are used to visualize specific data types, a short introduction to perceptual issues is given in Section 4.1. Furthermore, different issues, such as taxonomies for data, visual variables and their ability to express different data types, are discussed in Section 4.1. Section 4.2 focuses on general criteria used in information visualization and the use of metaphors. Section 4.3 presents a survey of different visualization techniques, mainly in the context of multivariate data, by discussing properties of different techniques related to their comprehensive and interaction properties, advantages, and drawbacks with illustrations given for different data sets. Section 4.4 provides an overview of existing evaluations on visualization techniques designed for graphs and trees. The survey mainly focuses on the effect of graph layout algorithms which compute the position of nodes and edges, as well as on user’s understanding of graphs for different tasks. Section 4.5 covers several issues concerning multiple view visualizations. Apart from a classification of multiple view instances, design-issues are discussed. The section is concluded with a comparison based on evaluation studies between multiple views and integrated views.
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