47,358 research outputs found

    The State-of-the-Art of Set Visualization

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    Sets comprise a generic data model that has been used in a variety of data analysis problems. Such problems involve analysing and visualizing set relations between multiple sets defined over the same collection of elements. However, visualizing sets is a non-trivial problem due to the large number of possible relations between them. We provide a systematic overview of state-of-the-art techniques for visualizing different kinds of set relations. We classify these techniques into six main categories according to the visual representations they use and the tasks they support. We compare the categories to provide guidance for choosing an appropriate technique for a given problem. Finally, we identify challenges in this area that need further research and propose possible directions to address these challenges. Further resources on set visualization are available at http://www.setviz.net

    A Visual Stack Based Paradigm for Visualization Environments

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    We present a new visual paradigm for Visualization Systems, inspired by stack-based programming. Most current implementations of Visualization systems are based on directional graphs. However directional graphs as a visual representation of execution, though initially quite intuitive, quickly grow cumbersome and difficult to follow under complex examples. Our system presents the user with a simple and compact methodology of visually stacking actions directly on top of data objects as a way of creating filter scripts. We explore and address extensions to the basic paradigm to allow for: multiple data input or data output objects to and from execution action modules, execution thread jumps and loops, encapsulation, and overall execution control. We exploit the dynamic nature of current computer graphic interfaces by utilizing features such as drag-and-drop, color emphasis and object animation to indicate action, looping, message/parameter passing; to furnish an overall better understanding of the resulting laid out execution scripts

    The significance of information visualisation based on the symbolic semantics of Peking Opera Painted Faces (POPF)

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    Peking Opera as a branch of Chinese traditional cultures and arts has a very distinct colourful facial make-up for all actors in the stage performance. Such make-up is stylised in typical cultural elements which all combined together to form the painted faces to describe and symbolise the background and characteristic of specific roles. The Peking Opera Painted Faces (POPF) was taken as an example to study the information visualisation and transmission, to see how information and meanings can be effectively expressed through the colourful visual elements. In order to identify the state-of-the-art in the related Culture Inspired Design as one of the design principles, the literature resources including illustrations of POPF were investigated, and also the semantic features and elements of other similar forms of modern design which has close connection with multiple aspects of social life. The study has proved that the visual elements of POPF played the most effective role in the information transmittion. Future application of this culture resource may include product design, interaction design, system design and service design around the world

    Obvious: a meta-toolkit to encapsulate information visualization toolkits. One toolkit to bind them all

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    This article describes “Obvious”: a meta-toolkit that abstracts and encapsulates information visualization toolkits implemented in the Java language. It intends to unify their use and postpone the choice of which concrete toolkit(s) to use later-on in the development of visual analytics applications. We also report on the lessons we have learned when wrapping popular toolkits with Obvious, namely Prefuse, the InfoVis Toolkit, partly Improvise, JUNG and other data management libraries. We show several examples on the uses of Obvious, how the different toolkits can be combined, for instance sharing their data models. We also show how Weka and RapidMiner, two popular machine-learning toolkits, have been wrapped with Obvious and can be used directly with all the other wrapped toolkits. We expect Obvious to start a co-evolution process: Obvious is meant to evolve when more components of Information Visualization systems will become consensual. It is also designed to help information visualization systems adhere to the best practices to provide a higher level of interoperability and leverage the domain of visual analytics
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