From visual data exploration to visual data mining: a survey <s> Interaction <s> Considers how dynamic queries allow users to "fly through" databases by adjusting widgets and viewing the animated results. In studies, users reacted to this approach with an enthusiasm more commonly associated with video games. Adoption requires research into retrieval and display algorithms and user-interface design. The author discusses how experts may benefit from visual interfaces because they will be able to formulate more complex queries and interpret intricate results. > <s> BIB001 </s> From visual data exploration to visual data mining: a survey <s> Interaction <s> Much of the attention in visualization research has focussed on data rooted in physical phenomena, which is generally limited to three or four dimensions. However, many sources of data do not share this dimensional restriction. A critical problem in the analysis of such data is providing researchers with tools to gain insights into characteristics of the data, such as anomalies and patterns. Several visualization methods have been developed to address this problem, and each has its strengths and weaknesses. This paper describes a system named XmdvTool which integrates several of the most common methods for projecting multivariate data onto a two-dimensional screen. This integration allows users to explore their data in a variety of formats with ease. A view enhancement mechanism called an N-dimensional brush is also described. The brush allows users to gain insights into spatial relationships over N dimensions by highlighting data which falls within a user-specified subspace. > <s> BIB002 </s> From visual data exploration to visual data mining: a survey <s> Interaction <s> The purpose of visualization is to present information to human beings. Perceptually based visualization aims at making such presentation as efficient and effective as possible, from the human’s point of view. I.e., it seeks to maximize the amount of information that the human viewer can perceive out of the presentation. <s> BIB003 </s> From visual data exploration to visual data mining: a survey <s> Interaction <s> Interactive techniques are powerful tools for manipulating visualizations to analyze, communicate and acquire information. This is especially true for large data sets or complex 3D visualizations. Although many new types of interaction have been introduced recently, very little work has been done on understanding what their components are, how they are related and how they can be combined. This paper begins to address these issues with a framework for classifying interactive visualizations. Our goal is a framework that will enable us to develop toolkits for assembling visualization interfaces both interactively and automatically. <s> BIB004 </s> From visual data exploration to visual data mining: a survey <s> Interaction <s> Interactive selection is a critical component in exploratory visualization, allowing users to isolate subsets of the displayed information for highlighting, deleting, analysis, or focussed investigation. Brushing, a popular method for implementing the selection process, has traditionally been performed in either screen space or data space. We introduce the concept of a structure-based brush, which can be used to perform selection in hierarchically structured data sets. Our structure-based brush allows users to navigate hierarchies by specifying focal extents and level-of-detail on a visual representation of the structure. Proximity-based coloring, which maps similar colors to data that are closely related within the structure, helps convey both structural relationships and anomalies. We describe the design and implementation of our structure-based brushing tool. We also validate its usefulness using two distinct hierarchical visualization techniques, namely hierarchical parallel coordinates and tree-maps. <s> BIB005
Interaction techniques can empower the user's perception of information when visually exploring a data set BIB003 and virtually all visualization techniques are used combined with dynamics and interactivity. The ability to interact with visual representations can greatly reduce the drawbacks of the techniques, particularly those related to visual clutter and object overlap, providing the user with mechanisms for handling complexity in larger data sets. Keim  identifies two categories of interaction techniques. The first group is comprised of those that operate on the visual representations to allow visualization of a larger amount of data. Typically, many such techniques have been designed as an integrated component of tools targeted at specific domains and can actually be considered as visualization techniques themselves, such as FishEye Views for graph visualization and Hyperbolic Trees for visualization of hierarchies. The second category is comprised of techniques supporting a more effective data exploration by allowing dynamic or interactive mapping of data attributes to visualization parameters or direct interaction with visualization models, of which well-known examples are Linking-and-Brushing [23] , Dynamic Queries BIB001 , and Detail-on-Demand  . A discussion of brushing techniques and a description of an extension for interactive manipulation of hierarchical data representations is available in Fua et al. BIB005 . See also  for a short description of these and other interaction techniques and references. Chuah and Roth BIB004 define a comprehensive framework for user interface techniques used in visualization systems, building upon work in the field of user interface design targeted at characterizing user interfaces. The goal of such a framework is to establish grounds for comparison among different systems, reuse of previous design elements, and composition of interaction primitives to create new interfaces. They emphasize that different interaction functions, although achieving different effects, do share similar component basic interactions. They focus on the semantic level of interface design and introduce the Basic Visualization Interaction as the semantic primitive of their framework. Several visual data exploration systems resulted from work on visualization and interaction techniques, some of which are available for distribution as academic tools (such as XmdvTool BIB002 and XGobi 3 ), while others have evolved into commercial products (such as IVEE [1] , now SpotFire 4 ). Several Web-based resources list visualization and general data exploration software, see  for pointers to some.