Visualization

Abstract: Sorry no abstract available for this article

 Visualization;  analysis;  hci;  review;  tags;  infovis;  tagging;  

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Abstract: Both the Resource Description Framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.

 Visualization;  data integration;  semantic;  infovis;  data-mining;  rdf;  attribute inference;  

Abstract: One of the most challenging issues in mining information from the World Wide Web is the design of systems that present the data to the end user by clustering them into meaningful semantic categories. We show that the analysis of the results of a clustering engine can significantly take advantage of enhanced graph drawing and visualization techniques. We propose a graph-based user interface for Web clustering engines that makes it possible for the user to explore and visualize the different semantic categories and their relationships at the desired level of detail

 Visualization;  clustering;  web;  graph;  

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Abstract: Purpose - To describe how information visualization can be used in the design of interface tools for large-scale repositories. Design/methodology/approach - One challenge for designers in the context of large-scale repositories is to create interface tools that help users find specific information of interest. In order to be most effective, these tools need to leverage the cognitive characteristics of the target users. At the Los Alamos National Laboratory, the authors target users are scientists and engineers who can be characterized as higher-order, analytical thinkers. In this paper, the authors describe a visualization tool they have created for making the authors large-scale digital object repositories more usable for them: SearchGraph, which facilitates data set analysis by displaying search results in the form of a two- or three-dimensional interactive scatter plot. Findings - Using SearchGraph, users can view a condensed, abstract visualization of search results. They can view the same dataset from multiple perspectives by manipulating several display, sort, and filter options. Doing so allows them to see different patterns in the dataset. For example, they can apply a logarithmic transformation in order to create more scatter in a dense cluster of data points or they can apply filters in order to focus on a specific subset of data points. Originality/value - SearchGraph is a creative solution to the problem of how to design interface tools for large-scale repositories. It is particularly appropriate for the authors target users, who are scientists and engineers. It extends the work of the first two authors on ActiveGraph, a read-write digital library visualization tool.

 Visualization;  document;  information-retrieval;  infovis;  library;  

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Abstract: Sorry no abstract available for this article

 Visualization;  graph;  collaboration;  wiki;  Wikipedia;  revert;  user model;  

Abstract: We introduce a series of geographically weighted (GW) interactive graphics, or geowigs, and use them to explore spatial relationships at a range of scales. We visually encode information about geographic and statistical proximity and variation in novel ways through gw-choropleth maps, multivariate gw-boxplots, gw-shading and scalograms. The new graphic types reveal information about GW statistics at several scales concurrently. We impement these views in prototype software containing dynamic links and GW interactions that encourage exploration and refine them to consider directional geographies. An informal evaluation uses interactive GW techniques to consider Guerry’s dataset of moral statistics, casting doubt on correlations originally proposed through visual analysis, revealing new local anomalies and suggesting multivariate geographic relationships. Few attempts at visually synthesising geography with multivariate statistical values at multiple scales have been reported. The geowigs proposed here provide informative representations of multivariate local variation, particularly when combined with interactions that coordinate views and result in gw-shading. We argue that they are widely applicable to area and point-based geographic data and provide a set of methods to support visual analysis using GW statistics through which the effects of geography can be explored at multiple scales.

 Visualization;  exploratory data analysis;  scale;  infovis;  exploratory;  gwr;  interactive;  interaction;  geographical weighting;  multivariate;  directional;  coordinated views;  

Abstract: Sorry no abstract available for this article

 Visualization;  blog;  discovery;  

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Abstract: Sorry no abstract available for this article

 Visualization;  design;  analysis;  collaboration;  computer-supported cooperative work;  

Abstract: Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical ‘mashups’ in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial ‘tag clouds’, ‘tag maps’, ‘data dials’ and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the mashup approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.

 spatiotemporal;  Geovisualization;  Visualization;  infovis;  google;  

Abstract: Sorry no abstract available for this article

 Visualization;  network security;  intrusion detection;  data exploration;  

Abstract: Due to the growing interest in geospatial data mining and analysis, data cleaning and integration in geospatial data is becoming an important issue. Geospatial entity resolution is the process of reconciling multiple location references to the same real world location within a single data source (deduplication) or across multiple data sources (integration). In this paper, we introduce an interactive tool called GeoDDupe which effectively combines automatic data mining algorithms for geospatial entity resolution with a novel network visualization supporting users’ resolution analysis and decisions. We illustrate the GeoDDupe interface with an example geospatial dataset and show how users can efficiently and accurately resolve location entities. Finally, the case study with two real-world geospatial datasets demonstrates the potential of GeoDDupe.

 Visualization;  geocoding;  geospatial;  entities;  

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Abstract: We describe the design and deployment of Many Eyes, a public web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around visualizations at a large scale by fostering a social style of data analysis in which visualizations not only serve as a discovery tool for individuals but also as a medium to spur discussion among users. To support this goal, the site includes novel mechanisms for end-user creation of visualizations and asynchronous collaboration around those visualizations. In addition to describing these technologies, we provide a preliminary report on the activity of our users.

 Visualization;  World Wide Web;  social data analysis;  social software;  communication-minded visualization;  

Abstract: Michottes theory of ampliation suggests that causal relationships are perceived by objects animated under appropriate spatiotemporal conditions. We extend the theory of ampliation and propose that the immediate perception of complex causal relations is alsodependent on a set of structural and temporal rules. We designed animated representations, based on Michottes rules, for showing complex causal relationships or causal semantics. In this paper we describe a set of animations for showing semantics such as causal amplification, causal strength, causal dampening, and causal multiplicity. In a two part study we compared the effectiveness of both the static and animated representations. The first study (N=44) asked participants to recall passages that were previously displayed using both types of representations. Participants were 8% more accurate in recalling causal semantics when theywere presented using animations insteadof static graphs. In the second study (N=112) we evaluated the intuitiveness of the representations. Our results showed that while users were as accurate with the static graphs as with the animations, theywere 9% faster in matching the correct causal statements in the animated condition. Overall our results show that animated diagrams that are designed based on perceptual rules such as those proposed by Michotte have the potential to facilitate comprehension of complex causal relations.

 semantics;  Visualization;  perception;  causality;  animated graphs;  visualizing cause and effect;  graph semantics;  

Abstract: Sorry no abstract available for this article

 Visualization;  time representation;  

Abstract: Sorry no abstract available for this article

 Visualization;  cartography;  context;  openstandards;  

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Abstract: In many applications, it is impor tant to understand the individual values of, and relationships between, multiple related scalar variables defined across a common domain. Several approaches have been proposed for representing data in these situations. In this paper we focus on strategies for the visualization of multivariate data that rely on color mixing. In par ticular, through a series of controlled obser ver experiments, we seek to establish a fundamental understanding of the information-carr ying capacities of two alternative methods for encoding multivariate information using color : color blending and color weaving. We begin with a baseline experiment in which we assess par ticipants abilities to accurately read numerical data encoded in six different basic color scales defined in the L*a*b* color space. We then assess par ticipants abilities to read combinations of 2, 3, 4 and 6 different data values represented in a common region of the domain, encoded using either color blending or color weaving. In color blending a single mixed color is formed via linear combination of the individual values in L*a*b* space, and in color weaving the original individual colors are displayed side-by-side in a high frequency texture that fills the region. A third experiment was conducted to clarify some of the trends regarding the color contrast and its effect on the magnitude of the error that was obser ved in the second experiment. The results indicate that when the component colors are represented side-by-side in a high frequency texture, most par ticipants abilities to infer the values of individual components are significantly improved, relative to when the colors are blended. Par ticipants performance was significantly better with color weaving par ticularly when more than 2 colors were used, and even when the individual colors subtended only 3 minutes of visual angle in the texture. However, the information-carr ying capacity of the color weaving approach has its limits. We found that par ticipants abilities to accurately inter pret each of the individual components in a high frequency color texture typically falls off as the number of components increases from 4 to 6. We found no significant advantages, in either color blending or color weaving, to using color scales based on component hues thatare more widely separated in the L*a*b* color space. Fur thermore, we found some indications that extra difficulties may arise when opponent hues are employed.

 Visualization;  perception;  color;  color weaving;  color blending;  

Abstract: Understanding how people use online maps allows data acquisition teams to concentrate their efforts on the portions of the map that are most seen by users. Online maps represent vast databases, and so it is insufficient to simply look at a list of the most-accessed URLs. Hotmap takes advantage of the design of a mapping systems imagery pyramid to superpose a heatmap of the log files over the original maps. Users behavior within the system can be observed and interpreted. This paper discusses the imagery acquisition task that motivated Hotmap, and presents several examples of information that Hotmap makes visible. we discuss the design choices behind Hotmap, including logarithmic color schemes; low-saturation background images; and tuning images to explore both infrequently-viewed and frequently-viewed spaces.

 GIS;  Geography;  Visualization;  maps;  infovis;  web20;  geospatial;  vast;  social navigation;  geographical visualization;  heatmap;  server log analysis;  online mapping systems;  

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Abstract: Interactive animated images are often the only means to explore large time series of meteorological data sets. However, despite being interactive, animations still lead to information overload. We firstly look at the factors limiting the exploratory use of animations for studies of precipitating cloud and argue that two main factors are responsible for that: data complexity and animation design based on images that mimic reality. Then we present an example of how the current approach to visualize time series of meteorological images can be improved by computational methods, particularly by feature tracking. Next, we describe the visualization environment and discuss the representational, data mining and interactive functionality resulting from such a combination in an environment that is specifically dedicated to visual exploration and analysis of precipitating clouds.

 Visualization;  exploration;  temporal;  

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Abstract: This paper describes Show Me, an integrated set of user interface commands and defaults that incorporate automatic presentation into a commercial visual analysis system called Tableau. A key aspect of Tableau is VizQL, a language for specifying views, which is used by Show Me to extend automatic presentation to the generation of tables of views (commonly called small multiple displays). A key research issue for the commercial application of automatic presentation is the user experience, which must support the flow of visual analysis. User experience has not been the focus of previous research on automatic presentation. The Show Me user experience includes the automatic selection of mark types, a command to add a single field to a view, and a pair of commands to build views for multiple fields. Although the use of these defaults and commands is optional, user interface logs indicate that Show Me is used by commercial users.

 Visualization;  analysis;  infovis;  vast;  small multiples;  automatic presentation;  visual analysis;  graphic design;  best practices;  data visualization;  

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Abstract: In many situations, individuals or groups of individuals are faced with the need to examine sets of documents to achieve understanding of their structure and to locate relevant information. In that context, this paper presents a framework for visual text mining to support exploration of both general structure and relevant topics within a textual document collection. Our approach starts by building a visualization from the text data set. On top of that, a novel technique is presented that generates and filters association rules to detect and display topics from a group of documents. Results have shown a very consistent match between topics extracted using this approach to those actually present in the data set.

 Visualization;  text;  data-mining;  

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Abstract: This paper presents scented widgets, graphical user interface controls enhanced with embedded visualizations that facilitate navigation in information spaces. We describe design guidelines for adding visual cues to common user interface widgets such as radio buttons, sliders, and combo boxes and contribute a general software framework for applying scented widgets within applications with minimal modifications to existing source code. We provide a number of example applications and describe a controlled experiment which finds that users exploring unfamiliar data make up to twice as many unique discoveries using widgets imbued with social navigation data. However, these differences equalize as familiarity with the data increases.

 Information Visualization;  Visualization;  infovis;  vast;  icons;  large dataset visualization;  text and document visualization;  multiresolution visualization;  geographic visualization;  applications of infovis;  user interface toolkits;  information foraging;  social navigation;  social data analysis;  

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Abstract: This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and archetypes. The strength of the approach comes from GEs sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation.The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

 Geography;  Visualization;  health;  infovis;  

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Abstract: In a world flooded by text of various sources, it is of strategic importance to find ways to map information present in written documents in a form that helps users locate and associate important information within a particular text data set. Content-based maps can support extremely useful explorations of text data sets. This paper proposes and evaluates the use of Kolmogorov complexity approximations as a means to detect similarity between general textual documents, in order to support mapping and visualization techniques for corpora exploration. The calculation of this similarity measure requires no intermediate representation of a corpus (such as vector representation) and therefore no pre-processing or parametrization steps. That makes it very attractive for a wider range of exploratory applications compared to conventional measures that need vector-based text representations. The visual layout used here is based on fast distance multi-dimensional projections. It is shown that the similarity measure and the resulting maps present very good precision and that the approach can be used successfully for visual analysis of automatically generated text maps.

 Visualization;  classification;  analysis;  document;  

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Abstract: Investigative analysts who work with collections of text documents connect embedded threads of evidence in order to formulate hypotheses about plans and activities of potential interest. As the number of documents and the corresponding number of concepts and entities within the documents grow larger, sense-making processes become more and more difficult for the analysts. We have developed a visual analytic system called Jigsaw that represents documents and their entities visually in order to help analysts examine reports more efficiently and develop theories about potential actions more quickly. Jigsaw provides multiple coordinated views of document entities with a special emphasis on visually illustrating connections between entities across the different documents.

 Visualization;  knowledge management;  analysis;  infovis;  vast;  knowledge-management;  

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Abstract: Tasks in visual analytics differ from typical information retrieval tasks in fundamental ways. A critical part of a visual analytics is to ask the right questions when dealing with a diverse collection of information. In this article, we introduce the design and application of an integrated exploratory visualization system called Storylines. Storylines provides a framework to enable analysts visually and systematically explore and study a body of unstructured text without prior knowledge of its thematic structure. The system innovatively integrates latent semantic indexing, natural language processing, and social network analysis. The contributions of the work include providing an intuitive and directly accessible representation of a latent semantic space derived from the text corpus, an integrated process for identifying salient lines of stories, and coordinated visualizations across a spectrum of perspectives in terms of people, locations, and events involved in each story line. The system is tested with the 2006 VAST contest data, in particular, the portion of news articles.

 Visualization;  analysis;  exploration;  text;  vast;  narrative;  nevac;  

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Abstract: Investigative analysts who work with collections of text documents connect embedded threads of evidence in order to formulate hypotheses about plans and activities of potential interest. As the number of documents and the corresponding number of concepts and entities within the documents grow larger, sense-making processes become more and more difficult for the analysts. We have developed a visual analytic system called Jigsaw that represents documents and their entities visually in order to help analysts examine reports more efficiently and develop theories about potential actions more quickly. Jigsaw provides multiple coordinated views of document entities with a special emphasis on visually illustrating connections between entities across the different documents.

 Visualization;  knowledge management;  analysis;  infovis;  vast;  knowledge-management;  

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Abstract: The analysis of time-oriented data is an important task in many application scenarios. In recent years, a variety of techniques for visualizing such data have been published. This variety makes it difficult for prospective users to select methods or tools that are useful for their particular task at hand. In this article, we develop and discuss a systematic view on the diversity of methods for visualizing time-oriented data. With the proposed categorization we try to untangle the visualization of time-oriented data, which is such an important concern in Visual Analytics. The categorization is not only helpful for users, but also for researchers to identify future tasks in Visual Analytics.

 Visualization;  temporal;  

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Abstract: Tag clouds provide an aggregate of tag-usage statistics. They are typically sent as in-line HTML to browsers. However, display mechanisms suited for ordinary text are not ideal for tags, because font sizes may vary widely on a line. As well, the typical layout does not account for relationships that may be known between tags. This paper presents models and algorithms to improve the display of tag clouds that con- sist of in-line HTML, as well as algorithms that use nested tables to achieve a more general 2-dimensional layout in which tag relationships are considered. The first algorithms leverage prior work in typesetting and rectangle packing, whereas the second group of algorithms leverage prior work in Electronic Design Automation. Experiments show our algorithms can be efficiently implemented and perform well.

 Visualization;  infovis;  tagging;  

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Abstract: We present a study of anonymized data capturing high-level communication activities within the Microsoft Instant Messenger network. We analyze properties of the communication network defined by user interactions and demographics, as reported and as derived from one month of data collected in June 2006. The compressed dataset occupies 4.5 terabytes, composed from 1 billion conversations per day (150 gigabytes) over one month of logging. The dataset contains more than 30 billion conversations among 240 million people. We focus on analyses of high-level characteristics and patterns that emerge from the collective dynamics of 240 million people, rather than the actions and characteristics of individuals. Analyses center on numbers and durations of conversations; the content of communications was neither available nor pursued. From the data we construct a communication graph with 190 million nodes and 1.3 billion undirected edges. We find that the graph is well connected, with an effective diameter of 7.8, and is highly clustered, with a clustering coefficient decaying slowly with exponent −0.4. We also find strong influences of homophily in activities, where people with similar characteristics overall tend to communicate more with one another, with the exception of gender, where we find cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.

 Visualization;  analysis;  networks;  social network;  services;  small-world;  software;  

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Abstract: In this article, we reiterate the characteristics that make the rainbow color map a poor choice, provide examples that clearly illustrate these deficiencies even on simple data sets, and recommend better color maps for several categories of display. The goal is to make the rainbow color map as rare in visualization as the goto statement is in programming - which complicates the task of analyzing and verifying program correctness

 Visualization;  color;  

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Abstract: Sorry no abstract available for this article

 Visualization;  user testing;  

Abstract: Visualization tools are typically evaluated in controlled studies that observe the short-term usage of these tools by participants on preselected data sets and benchmark tasks. Though such studies provide useful suggestions, they miss the long-term usage of the tools. A longitudinal study of a bioinformatics data set analysis is reported here. The main focus of this work is to capture the entire analysts process that an analyst goes through from a raw data set to the insights sought from the data. The study provides interesting observations about the use of visual representations and interaction mechanisms provided by the tools, and also about the process of insight generation in general. This deepens our understanding of visual analytics, guides visualization developers in creating more effective visualization tools in terms of user requirements, and guides evaluators in designing future studies that are more representative of insights sought by users from their data sets

 Visual Analytics;  Visualization;  infovis;  

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Abstract: Sorry no abstract available for this article

 Visualization;  infovis;  data;  interesting;  statistical;  interaction;  cognitive;  intelligent;  preception;  

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Abstract: Sorry no abstract available for this article

 Visualization;  virtual environment;  analysis paper;  

Abstract: Sorry no abstract available for this article

 Visualization;  perception;  cartography;  

Abstract: This paper defines a new method of attribute uncertainty representation, the blinking region. It specifically communicates uncertainty in values associated with choropleth map regions. In this way, error and attribute (census) data can be made to alternate in the user’s view, communicating both datasets. The blinking region uncertainty visualization was tested via a web-based survey. Results show that it outperforms most current visualisation of attribute uncertainty techniques (e.g. image sharpness) in terms of visual appeal, speed of comprehension and overall effectiveness. Theoretically, regions that have the most attribute error could flicker at the fastest rate, with speed of blinking being proportional to the error.

 Visualization;  uncertainty;  spatial;  

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Abstract: We describe a framework for automatically selecting a summary set of photos from a large collection of geo-referenced photographs. Such large collections are inherently difficult to browse, and become excessively so as they grow in size, making summaries an important tool in rendering these collections accessible. Our summary algorithm is based on spatial patterns in photo sets, as well as textual-topical patterns and user (photographer) identity cues. The algorithm can be expanded to support social, temporal, and other factors. The summary can thus be biased by the content of the query, the user making the query, and the context in which the query is made. A modified version of our summarization algorithm serves as a basis for a new map-based visualization of large collections of geo-referenced photos, called Tag Maps. Tag Maps visualize the data by placing highly representative textual tags on relevant map locations in the viewed region, effectively providing a sense of the important concepts embodied in the collection. An initial evaluation of our implementation on a set of geo-referenced photos shows that our algorithm and visualization perform well, producing summaries and views that are highly rated by users.

 Visualization;  algorithm;  georeferencing;  flickr;  automated;  

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Abstract: Sorry no abstract available for this article

 Visual Analytics;  Visualization;  visual knowledge discovery;  collaborative and distributed;  data management and knowledge representation;  

Abstract: Sorry no abstract available for this article

 Software Engineering;  Visualization;  formal methods;  programming languages;  

Abstract: Sorry no abstract available for this article

 Visualization;  decision support systems;  geog 597 I;  

Abstract: Sorry no abstract available for this article

 Data mining;  Visualization;  data discovery;  geo-computation;  stnexus;  

Abstract: Sorry no abstract available for this article

 Visualization;  data visualisation;  decision support systems;  Knowledge Representation;  knowledge domain mapping, semantics;  

Abstract: Sorry no abstract available for this article

 Visualization;  

Abstract: Sorry no abstract available for this article

 Visualization;  time visualization;  

Abstract: Recent years have witnessed the dramatic popularity of online social networking services, in which millions of members publicly articulate mutual friendship relations. Guided by ethnographic research of these online communities, we have designed and implemented a visualization system for playful end-user exploration and navigation of large scale online social networks. Our design builds upon familiar node link network layouts to contribute customized techniques for exploring connectivity in large graph structures, supporting visual search and analysis, and automatically identifying and visualizing community structures. Both public installation and controlled studies of the system provide evidence of the systems usability, capacity for facilitating discovery, and potential for fun and engaged social activity.

 Data mining;  Visualization;  social networks;  exploration;  graphs;  community;  play;  

Abstract: Sorry no abstract available for this article

 Visualization;  geog 597 I;  

Abstract: Sorry no abstract available for this article

 Visualization;  

Abstract: Sorry no abstract available for this article

 Visualization;  infovis;  temporal;  

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Abstract: Scientific visualization as currently understood and practiced is still a relatively new discipline. As a result, we visualization researches are not necessarily accustomed to undertaking the sorts of self-examinations that other scientists routinely undergo in relation to their work. Yet if we are to creat a disciplinary culture focused on matters of real scientific importance and committed to real progress, it is essential that we ask ourselves hard questions on an ongoing basis. What are the most important research issues facing us? What underlying assumptions needs to be challenged and perhaps abandoned? What practices need to be reviewed? In this article, I attempt to start a discussion of these issues by proposing a list of top research problems and issues in scientific visualization.

 Visualization;  infovis;  

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Abstract: Sorry no abstract available for this article

 Visualization;  categorization;