Systematic Variation of Preattentive Attributes to Highlight Relevant Data in Information Visualization

In information visualization (InfoVis), the Visualizers (graph designers and creators) have to consider multiple parameters, such as colors and graphic symbols, to obtain a chart that correctly represents a data set. Along with this, visualizers must adequately select the combination of these range of parameters to drive the observers’ attention to the relevant data. When a visualizer drives the attention to relevant aspects of the information, she is providing a starting point to read the graph; this focus point might help the observer to complete the task faster and more efficiently, minimizing distraction from unimportant information. Contemporary tools for InfoVis help visualizers to a certain extent, but most of them currently do not provide insights or suggestions about the modifications needed to drive data attention. This article presents the preliminary results of an exploratory approach to draw the attention to some specific data subset selected by the graph creator, through a systematic variation of some preattentive attributes (i.e., color, texture and orientation). As a first simple method to validate the feasibility of the approach, a set of charts is created from the same source data, with exhaustive variations on preattentive attributes. All generated charts are then automatically evaluated using a salience map algorithm for data analysis images, to identify their focus attention point. After that, the algorithm chooses the chart that best emphasizes the data subset initially specified by the visualizer. To validate our approach, we have implemented a prototype tool, and preliminary results confirm that it is possible to systematically change the attention area of a chart

Saliency Prediction in the Data Visualization Design Process

L'abstract è presente nell'allegato / the abstract is in the attachmen

Attention and visual memory in visualization and computer graphics

Abstract—A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we “see ” details in an image can directly impact a viewer’s efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics

Considerations of Graphical Proximity and Geographical Nearness

"Near things are more similar than more distant things" states Tobler\u27s first law of geography. This seems obvious and is part to much cognitive research into the perception of the environment. The statement\u27s validity for assessments of geographical nearness purely from map symbols has yet to be ascertained. This paper considers this issue through a theoretical framework grounded in Gestalt concepts, behavioral ecological psychology and information psychology. It sets out to consider how influential experience or training may be on the association of graphical proximity with geographical nearness. A pilot study presents some initial findings. The findings regarding the influence of experience or training are ambiguous, but point to the rapid acquisition of affordances in the survey instruments as another factor for future research

A Theoretical Approach Towards Designing InfoVis for Decision Support Effectiveness

t—Information Visualization (InfoVis) as information systems used in gaining insights of large and multidimensional dataset has gained interest of human computer interaction researchers.The researchers have also craved for more theorybased design models to support designing InfoVis and to enhance its decision support effectiveness.This is a result of the observed insufficiency in the theoretical explanation and model of InfoVis design generally, and its decision support effectiveness, specifically.Extant literature reviewed showed that there is lack of studies that explicitly state the linkage between InfoVis design techniques and respective supporting theories, and how this translate to decision support design of InfoVis.This study therefore employs an unobtrusive research method that involves thematic analysis of InfoVis design and related theoretical literatures, to characterize, categorize and link the InfoVis theories with their respective design techniques.The result is a proposed theoretical design model.The model is therefore used, as a validation process, in the design of StudentViz – an InfoVis to support the multidimensionality of students’ dataset

A Theoretical Approach Towards Designing InfoVis for Decision Support Effectiveness

Information Visualization (InfoVis) as information systems used in gaining insights of large and multidimensional dataset has gained interest of human computer interaction researchers. The researchers have also craved for more theorybased design models to support designing InfoVis and to enhance its decision support effectiveness. This is a result of the observed insufficiency in the theoretical explanation and model of InfoVis design generally, and its decision support effectiveness, specifically. Extant literature reviewed showed that there is lack of studies that explicitly state the linkage between InfoVis design techniques and respective supporting theories, and how this translate to decision support design of InfoVis. This study therefore employs an unobtrusive research method that involves thematic analysis of InfoVis design and related theoretical literatures, to characterize, categorize and link the InfoVis theories with their respective design techniques. The result is a proposed theoretical design model. The model is therefore used, as a validation process, in the design of StudentViz – an InfoVis to support the multidimensionality of students’ dataset

CacophonyViz: Visualisation of Birdsong Derived Ecological Health Indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

Package Fingerprint: a visual summary of package interfaces and relationships

International audienceContext: Object-oriented languages such as Java, Smalltalk, and C++ structure their programs using packages. Maintainers of large systems need to understand how packages relate to each other, but this task is complex because packages often have multiple clients and play different roles (class container, code ownership. . . ). Several approaches have been proposed, among which the use of cohesion and coupling metrics. Such metrics help identify candidate packages for restructuring; however, they do not help maintainers actually understand the structure and interrelation- ships between packages. Objectives: In this paper, we use pre-attentive processing as the basis for package visualization and see to what extent it could be used in package understanding. Method: We present the package fingerprint, a 2D visualization of the references made to and from a package. The proposed visualization offers a semantically rich, but compact and zoomable views centered on packages. We focus on two views (incoming and outgoing references) that help users understand how the package under analysis is used by the system and how it uses the system. Results: We applied these views on four large systems: Squeak, JBoss, Azureus, and ArgoUML. We obtained several interesting results, among which, the identification of a set of recurring visual patterns that help maintainers: (a) more easily identify the role of and the way a package is used within the system (e.g., the package under analysis provides a set of layered services), and, (b) detect either problematic situations (e.g., a single package that groups together a large number of basic services) or opportunities for better package restructuring (e.g., removing cyclic dependencies among packages). The visualization generally scaled well and the detection of different patterns was always possible. Conclusion: The proposed visualizations and patterns proved to be useful in understanding and maintaining the different systems we addressed. To generalize to other contexts and systems, a real user study is required