A framework of interaction costs in information visualization

Interaction cost is an important but poorly understood factor in visualization design. We propose a framework of interaction costs inspired by Norman’s Seven Stages of Action to facilitate study. From 484 papers, we collected 61 interaction-related usability problems reported in 32 user studies and placed them into our framework of seven costs: (1) Decision costs to form goals; (2) System-power costs to form system operations; (3) Multiple input mode costs to form physical sequences; (4) Physical-motion costs to execute sequences; (5) Visual-cluttering costs to perceive state; (6) View-change costs to interpret perception; (7) State-change costs to evaluate interpretation. We also suggested ways to narrow the gulfs of execution (2–4) and evaluation (5–7) based on collected reports. Our framework suggests a need to consider decision costs (1) as the gulf of goal formation.     

Mental models, cognitive dissonance and executive information systems' effectiveness

Abstract. Recently there has been interest in the interaction between executives' mental models and executive information systems (EIS). As stated by Rockart & De Long (1988), 'the most significant effect of computer support for executives may be in the enhanced mental models of the systems' users' (p. 130).
It is proposed that each interaction between the EIS and the executive will induce cognitive dissonance in the executive. The effect of the dissonance on the mental models will depend upon (a) whether the executive is in an exploratory mode or confirmatory mode and (b) whether the dissonance is below, within or above the threshold range.
Cognitive dissonance serves to instil an opportunity for the creation, confirmation, expansion or reconstruction of one's mental model (s). This increases the likelihood of the executive's effectiveness being enhanced by the EIS and thus would enable better decision making. On the other hand, it can also lead to the rejection of the EIS depending on the mode (exploratory or confirmatory) of the executives and the level of their conviction in their mental models.
An understanding of the cognitive dissonance threshold ranges of executives under different modes of operation is important to prevent rejection of the EIS at one extreme and unquestioning acceptance at the other extreme. Continuous learning engendered by cognitive dissonance within the threshold range, whether in the exploratory mode or the confirmatory mode, is essential tor sustaining the symbiotic relationship between the executive and the EIS. Controlling the level of dissonance within certain range limits would allow opportunities for the creation, confirmation, expansion or reconstruction of mental models and thus, through enhanced mental models, enable better decision making by the executive. This better decision making results in increased effectiveness.     

Qualitative economic reasoning: a disequilibrium perspective

Extending a qualitative simulation of a market-based equilibrium model, this paper demonstrates the technical applicability of partial simulation from a more realistic disequilibrium viewpoint, where a market cannot be cleared promptly and it is subject to quantity constraints of spillover from other imbalanced markets. Some well-known observations of disequilibrium economics such as the effectiveness of policy change in relation with disequilibrium regime are proven to be correct in qualitative reasoning and simulation.     

Toward a deeper understanding of the role of interaction in information visualization

Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.     

Graph visualization and navigation in information visualization: Asurvey

This is a survey on graph visualization and navigation techniques, as used in information visualization. Graphs appear in numerous applications such as Web browsing, state-transition diagrams, and data structures. The ability to visualize and to navigate in these potentially large, abstract graphs is often a crucial part of an application. Information visualization has specific requirements, which means that this survey approaches the results of traditional graph drawing from a different perspective     

Computational models for integrating linguistic and visual information: A survey

This paper surveys research in developing computational models for integrating linguistic and visual information. It begins with a discussion of systems which have been actually implemented and continues with computationally motivated theories of human cognition. Since existing research spans several disciplines (e.g., natural language understanding, computer vision, knowledge representation), as well as several application areas, an important contribution of this paper is to categorize existing research based on inputs and objectives. Finally, some key issues related to integrating information from two such diverse sources are outlined and related to existing research. Throughout, the key issue addressed is the correspondence problem, namely how to associate visual events with words and vice versa.     

Cognitive difficulties and access to information systems: an interaction design perspective

People with cognitive difficulties, including memory, sequencing and attentional difficulties, face barriers to the use of conventionally designed information systems. This paper explores some of the reasons for these barriers in terms of the expectations normally placed on the user’s cognitive abilities and background knowledge. In the paper, the design and evaluation of three information systems are reported. These systems go some way towards overcoming cognitive barriers, allowing access to the advantages of computers for people with dyslexia, and for older users with no background in computer use who were able to access both email and the World Wide Web through specially designed interfaces.

Stochastic reasoning, free energy, and information geometry

Belief propagation (BP) is a universal method of stochastic reasoning. It gives exact inference for stochastic models with tree interactions and works surprisingly well even if the models have loopy interactions. Its performance has been analyzed separately in many fields, such as AI, statistical physics, information theory, and information geometry. This article gives a unified framework for understanding BP and related methods and summarizes the results obtained in many fields. In particular, BP and its variants, including tree reparameterization and concave-convex procedure, are reformulated with information-geometrical terms, and their relations to the free energy function are elucidated from an information-geometrical viewpoint. We then propose a family of new algorithms. The stabilities of the algorithms are analyzed, and methods to accelerate them are investigated.     

Strategic reasoning about business models: a conceptual modeling approach

Strategic reasoning about business models is an integral part of service design. In fast moving markets, businesses must be able to recognize and respond strategically to disruptive change. They have to answer questions such as: what are the threats and opportunities in emerging technologies and innovations? How should they target customer groups? Who are their real competitors? How will competitive battles take shape? In this paper we define a strategic modeling framework to help understand and analyze the goals, intentions, roles, and the rationale behind the strategic actions in a business environment. This understanding is necessary in order to improve existing or design new services. The key component of the framework is a strategic business model ontology for representing and analyzing business models and strategies, using the i* agent and goal oriented methodology as a basis. The ontology introduces a strategy layer which reasons about alternative strategies that are realized in the operational layer. The framework is evaluated using a retroactive example of disruptive technology in the telecommunication services sector from the literature.     

3D visualization for building information models based upon IFC and WebGL integration

Multimedia Tools and Applications - Building Information Modeling (BIM) technology provides broad-ranging support of AEC (architecture, engineering, and construction) industry needs. The inclusion...     

Combining background information and a top-down model for computing salient objects

Predicting the salient object region in real scenes has progressed significantly in recent years. In this work, we propose a novel method for computing salient object regions by combining background information and a top-down visual saliency model, which is well-suited for locating category-specific salient objects in cluttered real scenes. First, we used a robust background measure to acquire clean saliency maps by optimizing background information. Second, we learned a top-down saliency object model by combining a class-specific codebook and conditional random fields (CRFs) during the training phase. Furthermore, our model used the locality-constrained linear codes as latent CRF variables. Finally, we computed salient object regions by combining the robust background measure and top-down model. Experimental results on the Graz-02 and PASCAL VOC2007 datasets show that our method creates much better saliency maps than current state-of-the-art methods.     

信息可视化和可视分析:挑战与机遇——北戴河信息可视化战略研讨会总结报告

由天津大学软件学院发起并召集,东北大学秦皇岛分校和燕山大学承办的信息可视化战略研讨会于2012年6月9～10日在北戴河成功举行.本文总结了此次会议的讨论内容和达成的共识,对当前信息可视化和可视分析领域的挑战和国际上这方面的研究方向做了大致的分析,并对今后信息可视化和可视分析的大方向提出一些建议,以及对具体行动提出一系列倡议.     

Approximate reasoning and possibilistic models in classification

We introduce some ideal from the theory of approximate reasoning and from possibility theory based on fuzzy sets. We shown how these ideas can form the basis for building classification models which enable one to use imprecise information in their construction.     

Query based visual analysis: spatio-temporal reasoning in computer vision

Two experimental systems for query-based visual analysis are described. The first simulates an image sequence of moving, dividing cells with simple rules and monitors significant visual events. The second processes single raw images of real cells. Both invoke appropriate processing using explicit knowledge to respond to user queries. It is proposed that this selectivity is an essential feature for any system to analyse raw image sequences of moving, dividing cells as the computational expense of allowing all possible processing to proceed is enormous. Processing as required by the query allows adaptive strategies (e.g. different resolutions and focal processing) to be utilized and gives an effective attentional control structure to the system.     

Data visualization via latent variables and mixture models: a brief survey

In the literature, data visualization is extensively studied via diverse parametric probabilistic distributions for the exploration of continuous, binary, and counting data. An overview of the existing methods for non-symmetric data matrices is presented in an unified framework via the Bernoulli law and binary variables. An extension to continuous or counting variables is available by using instead any another univariate distribution such as the Poisson or Gaussian one. Several approaches are possible when the model is with a distribution on the rows, the columns, the row clusters, the column clusters, the cells, the blocks, or a transformed matrix of the distances from the pairs of rows or columns. The objective functions are presented with their full expressions in separated sections, one for each method: Kohonen’s map and related methods of self-organizing maps, generative topographic mapping as a probabilistic self-organizing map, linear principal component analysis and related matricial methods (non-negative factorization, factorization), probabilistic parametric embedding, probabilistic latent semantic visualization, latent cluster position model, t-distributed stochastic neighbor embedding. The conclusion is a discussion of the contribution with perspectives.     

Compressed-domain visual saliency models: a comparative study

Computational modeling of visual saliency has become an important research problem in recent years, with applications in video quality estimation, video compression, object tracking, retargeting, summarization, and so on. While most visual saliency models for dynamic scenes operate on raw video, several models have been developed for use with compressed-domain information such as motion vectors and transform coefficients. This paper presents a comparative study of eleven such models as well as two high-performing pixel-domain saliency models on two eye-tracking datasets using several comparison metrics. The results indicate that highly accurate saliency estimation is possible based only on a partially decoded video bitstream. The strategies that have shown success in compressed-domain saliency modeling are highlighted, and certain challenges are identified as potential avenues for further improvement.

     

Analyzing, modelling, and specifying visual interaction

 This paper discusses the processes underlying human-computer visual interaction, thereby analysing the characteristics of visual interaction; a model and a theory of visual interaction, from which a formal specification of visual interactive systems that are trustable by their users can be derived, are also illustrated. Such a theory is called theory of visual sentences, since each message on the computer screen is described as a visual sentence, i.e., an element of a visual language that specifies the interaction. The concept of relational structure is introduced to take into account different kinds of relations which can exist among the characteristic patterns present in a visual sentence. A formal model of the dynamics of visual interaction is presented, which is specified as transformations of visual sentences, modelled through visual rewriting systems, and transformations of relational structures. Particular attention is given to usability issues so as to satisfy relevant features needed to allow non-ambiguity of interpretation, adequate communication, determinism and system viability. An example of visual interaction is given where an immunologist interacts with a simulation of the human immune system. This work was supported by the Italian Ministry of University and Research under the Research Project of National Interest “Specification, Design and Development of Visual Interactive Systems”.     

Dual-task performance in multimodal human-computer interaction: a psychophysiological perspective

This paper examines the psychophysiological effects of mental workload in single-task and dual-task human-computer interaction. A mental arithmetic task and a manual error correction task were performed both separately and concurrently on a computer using verbal and haptic input devices. Heart rate, skin conductance, respiration and peripheral skin temperature were recorded in addition to objective performance measures and self-report questionnaires. Analysis of psychophysiological responses found significant changes from baseline for both single-task and dual-task conditions. There were also significant psychophysiological differences between the mental arithmetic task and the manual error correction task, but no differences in questionnaire results. Additionally, there was no significant psychophysiological difference between performing only the mental arithmetic task and performing both tasks at once. These findings suggest that psychophysiological measures respond differently to different types of tasks and that they do not always agree with performance or with participants’ subjective feelings.