The term Visual Analytics has been around for almost five years by now, but still there are on-going discussions about what it actually is and in particular what is new about it. The core of our view on Visual Analytics is the new enabling and accessible analytic reasoning interactions supported by the combination of automated and visual analysis. In this paper, we outline the scope of Visual Analytics using two problem and three methodological classes in order to workout the need for and purpose of Visual Analytics. By examples of analytic reasoning interaction, the respective advan- tages and disadvantages of automated and visual analysis methods are explained leading to a glimpse into the future of how Visual Analytics methods will enable us to go beyond what is possible when separately using the two methods.

/pdf/visual-analytics-how-much-visualization-and-how-much-2y88ivwfjh.pdf

Visual analytics: how much visualization and how much analytics?

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper.

/pdf/web-gis-in-practice-ix-a-demonstration-of-geospatial-visual-3qcl8ru4ad.pdf

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

This chapter provides a comparative survey of computational models of psychological development. To understand how computational modeling can contribute to the study of psychological development, it is important to appreciate the enduring issues in developmental psychology. The most common computational techniques applied to psychological development are production systems, connectionist networks, dynamic systems, robotics, and Bayesian inference. The chapter discusses modeling in the areas of the balance scale, past tense, object permanence, artificial syntax, similarity-to-correlation shifts in category learning, discrimination-shift learning, concept and word learning, and abnormal development. Some of the models reviewed in this chapter simulated development with programmer designed parameter changes. Variations in such parameter settings were used to implement age-related changes in both connectionist and dynamic-systems models of the A-not-B error, the Cascade-Correlation (CC) model of discrimination-shift learning, all three models of the similarity-to-correlation shift, and the autism model.

/pdf/cognitive-modeling-for-cognitive-engineering-77594902wt.pdf

Cognitive Modeling for Cognitive Engineering

Researchers and practitioners across many fields would benefit from the ability to predict human search time in complex visual displays. However, a missing element in our ability to predict search time is our ability to quantify the exogenous attraction of visual objects in terms of their impact on search time. The current work represents an initial step in this direction. We present two experiments using a quadrant search task to investigate how exogenous and endogenous factors influence human visual search. In Experiment 1, we measure the oculomotor capture*or the tendency of a stimulus to elicit a saccade*of a salient quadrant under conditions in which the salient quadrant does not predict target location. Despite the irrelevance of quadrant salience, we find that subjects persist in making saccades towards the salient quadrant at above-chance levels. We then present a Bayesian-based ideal performer model that predicts search time and oculomotor capture when the salient quadrant never contains the search target. Experiment 2 tested the predictions of the ideal performer model and revealed human performance to be in close correspondence with the model. We conclude that, in our speeded search task, the influence of an exogenous attractor on saccades can be quantified in terms of search time costs and, when these costs are considered, both search time and search behaviour reflect a boundedly optimal adaptation to the cost structure of the environment. Please address all correspondence to Christopher W. Myers, Air Force Research Laboratory, 2558 Fifth Street Bldg. 852, Wright-Patterson, OH 45433, USA. E-mail: christopher.myers2@ wpafb.af.mil

/pdf/the-insistence-of-vision-why-do-people-look-at-a-salient-1ekv4et8lu.pdf

The insistence of vision: Why do people look at a salient stimulus when it signals target absence?

A visualization technique based on the ideas of scatter plot matrix, star diagrams and parallel coordinates plot is developed in this paper. The principles and algorithms of these visualizations are analyzed and compared from a geometrical perspective. It shows that the three coordinate-bused geometrical visualizations have a unified mathematical foundation and presentation ways thus can he combined into a single visualization that we call parallel dual plot. The new visualization is created by firstly transforming a scatter plot into a star glyph, and then the star glyph is presented by parallel coordinates. Thus, this approach provides a point-to-point mapping and effectively overcomes the over-plotting problem of parallel coordinates. Moreover, this technique has merits of simple algorithm and easy interpretation. Example of application is demonstrated at the end of this paper.

Parallel Dual Visualization of Multidimensional Multivariate Data

ISUAL analytics is the science of analytical reasoning supportedbyhighlyinteractivevisualinterfaces.People use visual analytics tools and techniques to synthesize information; derive insight from massive, dynamic, and often conflicting data; detect the expected and discover the unexpected; provide timely, defensible, and understandable assessments; and communicate assessments effectively for action. The issues stimulating this body of research provide a grandchallengeinscience:turninginformationoverloadinto the opportunity of the decade. Visual analytics requires interdisciplinary science beyond traditional scientific and information visualization to include statistics, mathematics, knowledge representation, management and discovery technologies, cognitive and perceptual sciences, decision sciences, and more. An important research agenda to develop the next generation suite of visual analytics technologies is described in the book Illuminating the Path: The Research and Development Agenda for Visual Analytics, which is available at http:// nvac.pnl.gov/agenda.stm. The papers in this special section address a number of the issues described in the visual analytics research agenda. They are grouped into five major areas: multidimensional data, graphs and networks, communication network analysis, space and time, and fundamentals. The first two papers address issues of visual analysis of multidimensional data. The first paper, “High-Dimensional

G.G. Robertson

Papers

Guest Editorial: Special Section on Visual Analytics