The Visual Display of Quantitative Information

Examples are discussed to show the differences among discriminant analysis, logistic regression, and multiple regression. Chapter 6, “Multivariate Analysis of Variance,” presents advantages of multivariate analysis of variance (MANOVA) over univariate analysis of variance (ANOVA), discusses assumptions of MANOVA, and assesses validations of MANOVA assumptions and model estimation. The authors also discuss post hoc tests of MANOVA and multivariate analysis of covariance. Chapter 7, “Conjoint Analysis,” explains what conjoint analysis does and how it is different from other multivariate techniques. Guidelines of selecting attributes, models, and methods of data collection are presented. Chapter 8, “Cluster Analysis,” studies objectives, roles, and limitations of cluster analysis. Two basic concepts: similarity and distance are discussed. The authors also discuss details of five most popular hierarchical algorithms (singlelinkage, complete-linkage, average-linkage, centroid method, Ward’s method) and three nonhierarchical algorithms (the sequential threshold method, the parallel threshold method, and the optimizing procedure). Profiles of clusters and guidelines for cluster validation are studied as well. Chapter 9, “Multidimensional Scaling and Correspondence Analysis,” introduces two interdependence techniques to display the relationships in the data. The book describes clearly and intuitively the differences between the two techniques and how these two techniques are performed. Chapters 10–12 cover topics in SEM. Chapter 10, “Structural Equation Modeling: An Introduction,” introduces SEM and related concepts such as exogenous, endogenous constructs, and so on, points out the differences between SEM and other multivariate techniques, overviews the decision process of SEM. Chapter 11, “Confirmatory Factor Analysis,” explains the differences between exploratory and confirmatory factor analysis, discusses how to construct, validate, and assess the goodness of fit of a measurement model in SEM by confirmatory factor analysis. Chapter 12, “Testing a Structural Model,” presents some methods of SEM in examining the relationships between latent constructs. The book is an excellent book for people in management and marketing. For the Technometrics audience, this book does not have much flavor of physical, chemical, and engineering sciences. For example, partial least squares, a very popular method in Chemometrics, is discussed but not as detailed as other techniques in the book. Furthermore, due to the amount of materials covered in the book, it might be inappropriate for someone who is new to multivariate analysis.

The Grammar of Graphics

Interactive technologies have changed - and continue to change - our world. We are living in an era of transformation driven by the Internet, hand-held computing, digital photography, interactive entertainment, and wireless communication technologies. But such transformations are nothing new. Adoption of many technologies has transformed our work, play, communication, and thought. It has also transformed our research and practice in the HCI community.CHI 2002 explores transforming technologies, looking back to the past and forward to the future. First, by reflecting on past (and current) technologies, we seek a better understanding of questions like: Why do some technologies succeed where others fail? How have economic and work conditions and leisure been changed? What roles have technologists, entrepreneurs, legislators, lawyers, and citizens played? We examine these issues especially as they relate to HCI, a young field that will celebrate its 20th anniversary at CHI 2002.Second, we look forward, examining emerging technologies and involving us all in shaping their progress. Profound HCI issues are raised as computer and communications technologies progress from portable to wearable to implantable, as the power and speed of technology increases and the cost decreases, and as the standard desktop graphical interface is augmented by mobile devices, tangible and mixed reality interfaces. In response, we ask: What role should HCI professionals play in the development and deployment of such profoundly transformative devices and the socio-technical systems surrounding them? How can we ensure usability and a regard for personal privacy? What is the role of the legal and political system can they "keep up" with technology, or do sufficiently compelling technologies simply push them aside.Third, in addition to looking outward, CHI 2002 has looked inward to the practices of our community. We used some new technologies to nudge the CHI conference in the direction of greater interactivity, turning attendees into participants. CHIplace.org, our interactive online forum, enables people to exchange ideas, offer suggestions, and preview conference content. As part of CHIs increasing emphasis on issues of interest to designers and usability practitioners, CHI 2002 features the Practitioners Special Track. Professional and student designers present portfolios of their work, and usability professionals reflect on the experiences they have gained with usability methods in practice. CHI 2002 also is proud to feature a two-day forum, the CHI 2002|AIGA Experience Design Forum. Held in collaboration with the Experience Design Group of AIGA, the American Institute of Graphic Arts, this forum serves as an in-depth, interdisciplinary exploration of issues in design and human-computer interaction.

CHI '02 Extended Abstracts on Human Factors in Computing Systems

Parallel hierarchies: A visualization for cross-tabulating hierarchical categories

Information visualizations are an efficient means to support the users in understanding large amounts of complex, interconnected data; user comprehension, however, depends on individual factors such as their cognitive abilities. The research literature provides evidence that user-adaptive information visualizations positively impact the users’ performance in visualization tasks. This study attempts to contribute toward the development of a computational model to predict the users’ success in visual search tasks from eye gaze data and thereby drive such user-adaptive systems. State-of-the-art deep learning models for time series classification have been trained on sequential eye gaze data obtained from 40 study participants’ interaction with a circular and an organizational graph. The results suggest that such models yield higher accuracy than a baseline classifier and previously used models for this purpose. In particular, a Multivariate Long Short Term Memory Fully Convolutional Network shows encouraging performance for its use in online user-adaptive systems. Given this finding, such a computational model can infer the users’ need for support during interaction with a graph and trigger appropriate interventions in user-adaptive information visualization systems. This facilitates the design of such systems since further interaction data like mouse clicks is not required.

Predicting Visual Search Task Success from Eye Gaze Data as a Basis for User-Adaptive Information Visualization Systems

Various visualization techniques for correlated multiple quantitative data sets, which allow a researcher to explore a character of content, are fairly common tools in the visual analysis. The available methods and techniques for a displaying of different diagram types, are suitable for a partial solution to this kind of a practical problem. This paper represents an overview for some existing tools and techniques, regarding the quantitative data visualization. As a key part of the paper, the design guidelines for a visual construction of correlated quantitative data values, which are mostly applicable for interactive techniques, are presented.

Design guidelines for correlated quantitative data visualizations

Polar coordinates have been widely used in various techniques of interactive data visualization. The spatial organization through circular and radial layouts is implemented in a wide range of statistical charts and plots and is applicable for space-filling techniques and for node-link-group diagrams. Different arrangements of dots, lines and areas in polar coordinates create grids for data distribution, aggregation and linking.This work is devoted to the study of visual notations of data and their relationships and proposes an outline of their application in designing node-link-group diagrams, in order to arrange the geometric solutions at functional and logical levels of the visual representation.

Towards intelligible graph data visualization using circular layout

The exploration of moderately dense networks is used in various challenges of visual data analysis. Frequently, the solutions lay in graph drawing, based on automatic forcedirected layout, which results in a spontaneous and irreproducible node-link diagram. Currently available approaches to improve its readability are generally oriented to finite rendering without providing to the analyst handy tools for post-layout manipulations. Enabling indirect manual control on visualizations through multi-step menus may appear difficult to learn and use. Thus, this problem requires a more intuitive way of solving. This paper presents an original toolset for userguided refinement of the force-directed graph layout, with a bias on pen-centric sketching techniques.

Sketch-Based Interactions for Untangling of Force-Directed Graphs

Structured user model data not only allow system personalization, but also may be of interest as a source for analysis: in particular, for the study of general trends and for the detection of anomalies in preferences and mutually-referenced features among different user models. Such sources are multidimensional and interrelated, and recently started to be represented as graph-based datasets. Among the most effective ways of studying such data is visual exploration based on data-driven graph drawing approaches: in particular, node-link and node-link-group diagrams. The paper provides an overview of advanced approaches to the graphical representation of multidimensional data derived from user modeling and presents a proposal for developing flexible and scalable user interfaces for the hypergraph-based visual exploration of relations within a user model (UM). Then, we propose these principles in the visualization of an existing adaptive system.

Vladimir Guchev

Papers

Design guidelines for correlated quantitative data visualizations

Towards intelligible graph data visualization using circular layout

Sketch-Based Interactions for Untangling of Force-Directed Graphs

Visual Annotations for Hybrid Graph-based User Model