taxonomy

Abstract: 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.

 Information Visualization;  taxonomy;  Visual Analytics;  interaction techniques;  interaction;  

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Abstract: 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.

 Information Visualization;  taxonomy;  Visual Analytics;  interaction techniques;  interaction;  

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Abstract: Information visualisation is about gaining insight into data through a visual representation. This data is often multivariate and increasingly, the datasets are very large. To help us explore all this data, numerous visualisation applications, both commercial and research prototypes, have been designed using a variety of techniques and algorithms. Whether they are dedicated to geo-spatial data or skewed hierarchical data, most of the visualisations need to adopt strategies for dealing with overcrowded displays, brought about by too much data to fit in too small a display space. This paper analyses a large number of these clutter reduction methods, classifying them both in terms of how they deal with clutter reduction and more importantly, in terms of the benefits and losses. The aim of the resulting taxonomy is to act as a guide to match techniques to problems where different criteria may have different importance, and more importantly as a means to critique and hence develop existing and new techniques.

 taxonomy;  clutter reduction;  information visualisation;  occlusion;  large datasets;  

Abstract: Existing system-level taxonomies of visualization tasks are geared more towards the design of particular representations than the facilitation of user analytic activity. We present a set of ten low-level analysis tasks that largely capture people��?s activities while employing information visualization tools for understanding data. To help develop these tasks, we collected nearly 200 sample questions from students about how they would analyze five particular data sets from different domains. The questions, while not being totally comprehensive, illustrated the sheer variety of analytic questions typically posed by users when employing information visualization systems. We hope that the presented set of tasks is useful for information visualization system designers as a kind of common substrate to discuss the relative analytic capabilities of the systems. Further, the tasks may provide a form of checklist for system designers

 Visualization Taxonomy;  knowledge discovery;  analytic acitivity;  taxonomy;  Analytic activity;  design;  evaluation;  Analytic activity, taxonomy, knowledge;  

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Abstract: Existing system-level taxonomies of visualization tasks are geared more towards the design of particular representations than the facilitation of user analytic activity. We present a set of ten low-level analysis tasks that largely capture people��?s activities while employing information visualization tools for understanding data. To help develop these tasks, we collected nearly 200 sample questions from students about how they would analyze five particular data sets from different domains. The questions, while not being totally comprehensive, illustrated the sheer variety of analytic questions typically posed by users when employing information visualization systems. We hope that the presented set of tasks is useful for information visualization system designers as a kind of common substrate to discuss the relative analytic capabilities of the systems. Further, the tasks may provide a form of checklist for system designers

 Visualization Taxonomy;  knowledge discovery;  analytic acitivity;  taxonomy;  Analytic activity;  design;  evaluation;  Analytic activity, taxonomy, knowledge;  

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Abstract: Examination of the systemic properties and forms of interaction that characterize classification and categorization reveals fundamental syntactic differences between the structure of classification systems and the structure of categorization systems. These distinctions lead to meaningful differences in the contexts within which information can be apprehended and influence the semantic information available to the individual. Structural and semantic differences between classification and categorization are differences that make a difference in the information environment by influencing the functional activities of an information system and by contributing to its constitution as an information environment. ABSTRACT FROM AUTHOR Copyright of Library Trends is the property of Library Trends and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)

 taxonomy;  INFORMATION resources management;  LIBRARY science;  

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Abstract: Software systems of today are frequently composed from prefabricated, heterogeneous components that provide complex functionality and engage in complex interactions. Existing research on component-based development has mostly focused on component structure, interfaces, and functionality. Recently, software architecture has emerged as an area that also places significant importance on component interactions, embodied in the notion of software connectors. However, the current level of understanding and support for connectors has been insufficient. This has resulted in their inconsistent treatment and a notable lack of understanding of what the fundamental building blocks of software interaction are and how they can be composed into more complex interactions. This paper attempts to address this problem. It presents a comprehensive classification framework and taxonomy of software connectors. The taxonomy is obtained through an extensive analysis of existing component interactions. The taxonomy is used both to understand existing software connectors and to suggest new, unprecedented connectors. We demonstrate the use of the taxonomy on the architecture of a large, existing system.

 taxonomy;  software architecture;  software connector;  classification;  

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Abstract: Immersive virtual environments (VEs) have potential in many application areas, but many complex VE systems exhibit usability and interaction problems. This is partly due to a lack of consideration or understanding of 3D interaction tasks and techniques. This paper proposes the systematic study of the design, evaluation, and application of VE interaction techniques. In this methodology, design and evaluation are based on a formal task analysis and categorization of techniques, using multiple performance measures. As a direct consequence of our use of this methodology, we also present a variety of novel designs and evaluation results with respect to interaction techniques for three common VE tasks.

 taxonomy;   Visualization Taxonomy;  

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Abstract: Sorry no abstract available for this article

 taxonomy;  Visualization;  infovis;