We introduce an information visualization technique, known as GreenCurve, for large multivariate sparse graphs that exhibit small-world properties. Our fractal-based design approach uses spatial cues to approximate the node connections and thus eliminates the links between the nodes in the visualization. The paper describes a robust algorithm to order the neighboring nodes of a large sparse graph by solving the Fiedler vector of its graph Laplacian, and then fold the graph nodes into a space-filling fractal curve based on the Fiedler vector. The result is a highly compact visualization that gives a succinct overview of the graph with guaranteed visibility of every graph node. GreenCurve is designed with the power grid infrastructure in mind. It is intended for use in conjunction with other visualization techniques to support electric power grid operations. The research and development of GreenCurve was conducted in collaboration with domain experts who understand the challenges and possibilities intrinsic to the power grid infrastructure. The paper reports a case study on applying GreenCurve to a power grid problem and presents a usability study to evaluate the design claims that we set forth.

The application of information visualization holds tremendous promise for the electric power industry, but its potential has so far not been sufficiently exploited by the visualization community. Prior work on visualizing electric power systems has been limited to depicting raw or processed information on top of a geographic layout. Little effort has been devoted to visualizing the physics of the power grids, which ultimately determines the condition and stability of the electricity infrastructure. Based on this assessment, we developed a novel visualization system prototype, GreenGrid, to explore the planning and monitoring of the North American Electricity Infrastructure. The paper discusses the rationale underlying the GreenGrid design, describes its implementation and performance details, and assesses its strengths and weaknesses against the current geographic-based power grid visualization. We also present a case study using GreenGrid to analyze the information collected moments before the last major electric blackout in the Western United States and Canada, and a usability study to evaluate the practical significance of our design in simulated real-life situations. Our result indicates that many of the disturbance characteristics can be readily identified with the proper form of visualization.

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

We present a novel visualization technique to align whole bacterial genomes with millions of nucleotides. Our basic design combines the descriptive power of pixel-based visualizations with the interpretative strength of digital image-processing filters. The innovative use of pixel enhancement techniques on pixel-based visualizations brings out the best of the recursive data patterns and further enhances the effectiveness of the visualization techniques. The result is a fast, versatile, and cost-effective analysis tool to reveal hidden structures that might lead to the discovery of functional identifications as well as phenotypic changes of whole bacterial genomes. Nine different whole bacterial genomes obtained from public genome banks are used to demonstrate our designs and prove their viability. Although the design of the new visualization technique is targeted at analyzing genomic sequences, we show with examples that it can be used to study other types of sequential data sets with a priori orders.

Information visualization extends the scope of scientific visualization from physical phenomena to informational entities. This broadening is a direct reflection of the needs expressed by industry, national security, health and other national agendas to include all forms of information within the information analysis processes. It includes: masses of text, forms, and documents; business, manufacturing, and scientific databases; videos; audio; imagery; and most importantly the interactions with all these media types used to enable an enhanced process of discovery understanding, and presentation of situation assessments. In order for information visualization to become a reality, a rich, flexible data infrastructure must be established. The paper defines the scope of information visualization, the emerging opportunities and uses, the related and supporting technologies, and presents a data infrastructure architecture. This architecture supports full distributed multimedia information spaces, including technologies such as information agents, metadata transformations, and local derived metadata management which turns data and information into knowledge.>

. Providing an effective tool for risk assessment of terrestrial environmental resources requires a decision support system which will combine scientific analysis and the decision-making process. The goal of such a system is to provide a scientifically-based method for establishing and evaluating the potential effects of a policy or decision. To meet this goal a computing platform must be established which can run interactively a diverse set of models representing environmental, atmospheric, economic and political issues, and provide an integrated visualized output for decision makers. The decision support tool must be able to manipulate and display disparate information at the appropriate scale, over time and space. Hierarchical modelling, integrated information management systems, geographical information systems, and visualization systems are enabling technologies which provide one possible framework for implementing an effective decision support system. An application-oriented approach was used to examine the requirements and relationships needed to integrate analytical models tightly into a general decision support system. Forest modelling and its relationships to global climate change were the specific application used to prototype such an integrated system. This article introduces the scope and goals established using this application-oriented approach to developing a decision support system for risk assessment of terrestrial environmental resources, TERRA-Vision. It identifies critical design issues, such as the scaling, inter-operability and presentation of information. The article presents a conceptual framework, a design methodology and software used to develop the TERRA-Vision proof-of-concept demonstration system. Lessons learned are provided as part of the conclusions and areas identify where prototype development validated the conceptual framework and provided valuable insight on key issues relating to the development of more generalized decision support platforms. Finally, the conceptual framework is extended to provide an effective method for the development of an integrated scientific analysis and decision-making process.

In the last decade most research and development in computer graphics has been in the output side. Input devices and techniques for communicating with graphic systems are now also becoming active research topics. To communicate the state-of-the-art and to identify the key research issues, SIGGRAPH sponsored a workshop on graphics interaction input techniques in June, 1982. The topics to be discussed include tools for building user interfaces, recent successes using those tools, human factors, generic interaction types, interaction techniques for raster systems and style-independent interaction techniques. The workshop will be summarized with an address on the current state-of-the-art and identification of the major research issues. In addition, selected participants will be asked to address the primary research issues.

article Free Access Share on On the organization of a remote low cost intelligent graphics terminal Authors: John C. Dill General Motors Corporation General Motors CorporationView Profile , James J. Thomas General Motors Corporation General Motors CorporationView Profile Authors Info & Claims ACM SIGGRAPH Computer GraphicsVolume 9Issue 1Spring 1975pp 1–8https://doi.org/10.1145/964963.563733Published:01 April 1975Publication History 7citation275DownloadsMetricsTotal Citations7Total Downloads275Last 12 Months13Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF