DevLan/vispubs huggingface dataset:
Time Tree: Exploring Time Changing Hierarchies
Authors: Stuart K. Card, Bongwon Suh, Bryan A. Pendleton, Bryan Heer, John W. Bodnar
Published at VAST, 2006

Intelligence analysis often involves the task of gathering information about an organization. Knowledge about individuals in an organization and their relationships, often represented as a hierarchical organization chart, is crucial for understanding the organization. However, it is difficult for intelligence analysts to follow all individuals in an organization. Existing hierarchy visualizations have largely focused on the visualization of fixed structures and can not effectively depict the evolution of a hierarchy over time. We introduce TimeTree, a novel visualization tool designed to enable exploration of a changing hierarchy. TimeTree enables analysts to navigate the history of an organization, identify events associated with a specific entity (visualized on a TimeSlider), and explore an aggregate view of an individual's career path (a CareerTree). We demonstrate the utility of TimeTree by investigating a set of scenarios developed by an expert intelligence analyst. The scenarios are evaluated using a real dataset composed of eighteen thousand career events from more than eight thousand individuals. Insights gained from this analysis are presented
Toward a Multi-Analyst, Collaborative Framework for Visual Analytics
Authors: Susan Brennan, Klaus Mueller 0001, Gregory J. Zelinsky, I. V. Ramakrishnan, David Scott Warren, Arie E. Kaufman
Published at VAST, 2006

We describe a framework for the display of complex, multidimensional data, designed to facilitate exploration, analysis, and collaboration among multiple analysts. This framework aims to support human collaboration by making it easier to share representations, to translate from one point of view to another, to explain arguments, to update conclusions when underlying assumptions change, and to justify or account for decisions or actions. Multidimensional visualization techniques are used with interactive, context-sensitive, and tunable graphs. Visual representations are flexibly generated using a knowledge representation scheme based on annotated logic; this enables not only tracking and fusing different viewpoints, but also unpacking them. Fusing representations supports the creation of multidimensional meta-displays as well as the translation or mapping from one point of view to another. At the same time, analysts also need to be able to unpack one another's complex chains of reasoning, especially if they have reached different conclusions, and to determine the implications, if any, when underlying assumptions or evidence turn out to be false. The framework enables us to support a variety of scenarios as well as to systematically generate and test experimental hypotheses about the impact of different kinds of visual representations upon interactive collaboration by teams of distributed analysts
User Interfaces for the Exploration of Hierarchical Multi-dimensional Data
Authors: Mark Sifer
Published at VAST, 2006

A variety of user interfaces have been developed to support the querying of hierarchical multi-dimensional data in an OLAP setting such as pivot tables and Polaris. They are used to regularly check portions of a dataset and to explore a new dataset for the first time. In this paper, we establish criteria for OLAP user interface capabilities to facilitate comparison. Two criteria are the number of displayed dimensions along which comparisons can be made and the number of dimensions that are viewable at once - visual comparison depth and width. We argue that interfaces with greater visual comparison depth support regular checking of known data by users that know roughly where to look, while interfaces with greater comparison width support exploration of new data by users that have no a priori starting point and need to scan all dimensions. Pivot tables and Polaris are examples of the former. The main contribution of this paper is to introduce a new scalable interface that uses parallel dimension axis which supports the latter, greater visual comparison width. We compare our approach to both table based and parallel coordinate based interfaces. We present an implementation of our interface SGViewer, user scenarios and provide an evaluation that supports the usability of our interface
VAST 2006 Contest - A Tale of Alderwood
Authors: Georges G. Grinstein, Theresa A. O'Connell, Sharon J. Laskowski, Catherine Plaisant, Jean Scholtz, Mark A. Whiting
Published at VAST, 2006

Visual analytics experts realize that one effective way to push the field forward and to develop metrics for measuring the performance of various visual analytics components is to hold an annual competition. The first visual analytics science and technology (VAST) contest was held in conjunction with the 2006 IEEE VAST Symposium. The competition entailed the identification of possible political shenanigans in the fictitious town of Alderwood. A synthetic data set was made available as well as tasks. We summarize how we prepared and advertised the contest, developed some initial metrics for evaluation, and selected the winners. The winners were invited to participate at an additional live competition at the symposium to provide them with feedback from senior analysts
Visual Analysis of Conflicting Opinions
Authors: Chaomei Chen, Fidelia Ibekwe-Sanjuan, Eric SanJuan, Chris E. Weaver
Published at VAST, 2006

Understanding the nature and dynamics of conflicting opinions is a profound and challenging issue. In this paper we address several aspects of the issue through a study of more than 3,000 Amazon customer reviews of the controversial bestseller The Da Vinci Code, including 1,738 positive and 918 negative reviews. The study is motivated by critical questions such as: what are the differences between positive and negative reviews? What is the origin of a particular opinion? How do these opinions change over time? To what extent can differentiating features be identified from unstructured text? How accurately can these features predict the category of a review? We first analyze terminology variations in these reviews in terms of syntactic, semantic, and statistic associations identified by TermWatch and use term variation patterns to depict underlying topics. We then select the most predictive terms based on log likelihood tests and demonstrate that this small set of terms classifies over 70% of the conflicting reviews correctly. This feature selection process reduces the dimensionality of the feature space from more than 20,000 dimensions to a couple of hundreds. We utilize automatically generated decision trees to facilitate the understanding of conflicting opinions in terms of these highly predictive terms. This study also uses a number of visualization and modeling tools to identify not only what positive and negative reviews have in common, but also they differ and evolve over time
Visual Analysis of Historic Hotel Visitation Patterns
Authors: Chris E. Weaver, David Fyfe, Anthony C. Robinson, Deryck W. Holdsworth, Donna Peuquet, Alan M. MacEachren
Published at VAST, 2006

Understanding the space and time characteristics of human interaction in complex social networks is a critical component of visual tools for intelligence analysis, consumer behavior analysis, and human geography. Visual identification and comparison of patterns of recurring events is an essential feature of such tools. In this paper, we describe a tool for exploring hotel visitation patterns in and around Rebersburg, Pennsylvania from 1898-1900. The tool uses a wrapping spreadsheet technique, called reruns, to display cyclic patterns of geographic events in multiple overlapping natural and artificial calendars. Implemented as an improvise visualization, the tool is in active development through a iterative process of data collection, hypothesis, design, discovery, and evaluation in close collaboration with historical geographers. Several discoveries have inspired ongoing data collection and plans to expand exploration to include historic weather records and railroad schedules. Distributed online evaluations of usability and usefulness have resulted in numerous feature and design recommendations
Visual Analytics of Paleoceanographic Conditions
Authors: Roberto Therón
Published at VAST, 2006

Decade scale oceanic phenomena like El Nino are correlated with weather anomalies all over the globe. Only by understanding the events that produced the climatic conditions in the past will it be possible to forecast abrupt climate changes and prevent disastrous consequences for human beings and their environment. Paleoceanography research is a collaborative effort that requires the analysis of paleo time-series, which are obtained from a number of independent techniques and instruments and produced by a variety of different researchers and/or laboratories. The complexity of these phenomena that consist of massive, dynamic and often conflicting data can only be faced by means of analytical reasoning supported by a highly interactive visual interface. This paper presents an interactive visual analysis environment for paleoceanography that permits to gain insight into the paleodata and allow the control and steering of the analytical methods involved in the reconstruction of the climatic conditions of the past
Visual Exploration of Spatio-temporal Relationships for Scientific Data
Authors: Bryan Mehta, Srinivasan Parthasarathy 0001, Raghu Machiraju
Published at VAST, 2006

Spatio-temporal relationships among features extracted from temporally-varying scientific datasets can provide useful information about the evolution of an individual feature and its interactions with other features. However, extracting such useful relationships without user guidance is cumbersome and often an error prone process. In this paper, we present a visual analysis system that interactively discovers such relationships from the trajectories of derived features. We describe analysis algorithms to derive various spatial and spatio-temporal relationships. A visual interface is presented using which the user can interactively select spatial and temporal extents to guide the knowledge discovery process. We show the usefulness of our proposed algorithms on datasets originating from computational fluid dynamics. We also demonstrate how the derived relationships can help in explaining the occurrence of critical events like merging and bifurcation of the vortices
Visualizing the Performance of Computational Linguistics Algorithms
Authors: Stephen G. Eick, Justin Mauger, Alan Ratner
Published at VAST, 2006

We have built a visualization system and analysis portal for evaluating the performance of computational linguistics algorithms. Our system focuses on algorithms that classify and cluster documents by assigning weights to words and scoring each document against high dimensional reference concept vectors. The visualization and algorithm analysis techniques include confusion matrices, ROC curves, document visualizations showing word importance, and interactive reports. One of the unique aspects of our system is that the visualizations are thin-client Web-based components built using SVG visualization components
ASK-graphView: a large scale graph visualization system
Authors: James Abello, Frank van Ham, Neeraj Krishnan
Published at InfoVis, 2006

We describe ASK-GraphView, a node-link-based graph visualization system that allows clustering and interactive navigation of large graphs, ranging in size up to 16 million edges. The system uses a scalable architecture and a series of increasingly sophisticated clustering algorithms to construct a hierarchy on an arbitrary, weighted undirected input graph. By lowering the interactivity requirements we can scale to substantially bigger graphs. The user is allowed to navigate this hierarchy in a top down manner by interactively expanding individual clusters. ASK-GraphView also provides facilities for filtering and coloring, annotation and cluster labeling
Balancing Systematic and Flexible Exploration of Social Networks
Authors: Adam Perer, Ben Shneiderman
Published at InfoVis, 2006

Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks
Complex Logarithmic Views for Small Details in Large Contexts
Authors: Joachim Böttger, Michael Balzer, Oliver Deussen
Published at InfoVis, 2006

Commonly known detail in context techniques for the two-dimensional Euclidean space enlarge details and shrink their context using mapping functions that introduce geometrical compression. This makes it difficult or even impossible to recognize shapes for large differences in magnification factors. In this paper we propose to use the complex logarithm and the complex root functions to show very small details even in very large contexts. These mappings are conformal, which means they only locally rotate and scale, thus keeping shapes intact and recognizable. They allow showing details that are orders of magnitude smaller than their surroundings in combination with their context in one seamless visualization. We address the utilization of this universal technique for the interaction with complex two-dimensional data considering the exploration of large graphs and other examples
Dynamic Map Labeling
Authors: Ken Been, Eli Daiches, Chee-Keng Yap
Published at InfoVis, 2006

We address the problem of filtering, selecting and placing labels on a dynamic map, which is characterized by continuous zooming and panning capabilities. This consists of two interrelated issues. The first is to avoid label popping and other artifacts that cause confusion and interrupt navigation, and the second is to label at interactive speed. In most formulations the static map labeling problem is NP-hard, and a fast approximation might have O(n log n) complexity. Even this is too slow during interaction, when the number of labels shown can be several orders of magnitude less than the number in the map. In this paper we introduce a set of desiderata for "consistent" dynamic map labeling, which has qualities desirable for navigation. We develop a new framework for dynamic labeling that achieves the desiderata and allows for fast interactive display by moving all of the selection and placement decisions into the preprocessing phase. This framework is general enough to accommodate a variety of selection and placement algorithms. It does not appear possible to achieve our desiderata using previous frameworks. Prior to this paper, there were no formal models of dynamic maps or of dynamic labels; our paper introduces both. We formulate a general optimization problem for dynamic map labeling and give a solution to a simple version of the problem. The simple version is based on label priorities and a versatile and intuitive class of dynamic label placements we call "invariant point placements". Despite these restrictions, our approach gives a useful and practical solution. Our implementation is incorporated into the G-Vis system which is a full-detail dynamic map of the continental USA. This demo is available through any browser
Enabling Automatic Clutter Reduction in Parallel Coordinate Plots
Authors: Geoffrey P. Ellis, Alan J. Dix
Published at InfoVis, 2006

We have previously shown that random sampling is an effective clutter reduction technique and that a sampling lens can facilitate focus+context viewing of particular regions. This demands an efficient method of estimating the overlap or occlusion of large numbers of intersecting lines in order to automatically adjust the sampling rate within the lens. This paper proposes several ways for measuring occlusion in parallel coordinate plots. An empirical study into the accuracy and efficiency of the occlusion measures show that a probabilistic approach combined with a 'binning' technique is very fast and yet approaches the accuracy of the more expensive 'true' complete measurement
FacetMap: A Scalable Search and Browse Visualization
Authors: Greg Smith, Mary Czerwinski, Brian Meyers, Daniel C. Robbins, George G. Robertson, Desney S. Tan
Published at InfoVis, 2006

The dominant paradigm for searching and browsing large data stores is text-based: presenting a scrollable list of search results in response to textual search term input. While this works well for the Web, there is opportunity for improvement in the domain of personal information stores, which tend to have more heterogeneous data and richer metadata. In this paper, we introduce FacetMap, an interactive, query-driven visualization, generalizable to a wide range of metadata-rich data stores. FacetMap uses a visual metaphor for both input (selection of metadata facets as filters) and output. Results of a user study provide insight into tradeoffs between FacetMap's graphical approach and the traditional text-oriented approach
Hierarchical Edge Bundles: Visualization of Adjacency Relations in Hierarchical Data
Authors: Danny Holten
Published at InfoVis, 2006

A compound graph is a frequently encountered type of data set. Relations are given between items, and a hierarchy is defined on the items as well. We present a new method for visualizing such compound graphs. Our approach is based on visually bundling the adjacency edges, i.e., non-hierarchical edges, together. We realize this as follows. We assume that the hierarchy is shown via a standard tree visualization method. Next, we bend each adjacency edge, modeled as a B-spline curve, toward the polyline defined by the path via the inclusion edges from one node to another. This hierarchical bundling reduces visual clutter and also visualizes implicit adjacency edges between parent nodes that are the result of explicit adjacency edges between their respective child nodes. Furthermore, hierarchical edge bundling is a generic method which can be used in conjunction with existing tree visualization techniques. We illustrate our technique by providing example visualizations and discuss the results based on an informal evaluation provided by potential users of such visualizations
IPSep-CoLa: An Incremental Procedure for Separation Constraint Layout of Graphs
Authors: Tim Dwyer, Yehuda Koren, Kim Marriott
Published at InfoVis, 2006

We extend the popular force-directed approach to network (or graph) layout to allow separation constraints, which enforce a minimum horizontal or vertical separation between selected pairs of nodes. This simple class of linear constraints is expressive enough to satisfy a wide variety of application-specific layout requirements, including: layout of directed graphs to better show flow; layout with non-overlapping node labels; and layout of graphs with grouped nodes (called clusters). In the stress majorization force-directed layout process, separation constraints can be treated as a quadratic programming problem. We give an incremental algorithm based on gradient projection for efficiently solving this problem. The algorithm is considerably faster than using generic constraint optimization techniques and is comparable in speed to unconstrained stress majorization. We demonstrate the utility of our technique with sample data from a number of practical applications including gene-activation networks, terrorist networks and visualization of high-dimensional data.
MatrixExplorer: a Dual-Representation System to Explore Social Networks
Authors: Nathalie Henry Riche, Jean-Daniel Fekete
Published at InfoVis, 2006

MatrixExplorer is a network visualization system that uses two representations: node-link diagrams and matrices. Its design comes from a list of requirements formalized after several interviews and a participatory design session conducted with social science researchers. Although matrices are commonly used in social networks analysis, very few systems support the matrix-based representations to visualize and analyze networks. MatrixExplorer provides several novel features to support the exploration of social networks with a matrix-based representation, in addition to the standard interactive filtering and clustering functions. It provides tools to reorder (layout) matrices, to annotate and compare findings across different layouts and find consensus among several clusterings. MatrixExplorer also supports node-link diagram views which are familiar to most users and remain a convenient way to publish or communicate exploration results. Matrix and node-link representations are kept synchronized at all stages of the exploration process
Measuring Data Abstraction Quality in Multiresolution Visualizations
Authors: Qingguang Cui, Matthew O. Ward, Elke A. Rundensteiner, Jing Yang 0001
Published at InfoVis, 2006

Data abstraction techniques are widely used in multiresolution visualization systems to reduce visual clutter and facilitate analysis from overview to detail. However, analysts are usually unaware of how well the abstracted data represent the original dataset, which can impact the reliability of results gleaned from the abstractions. In this paper, we define two data abstraction quality measures for computing the degree to which the abstraction conveys the original dataset: the histogram difference measure and the nearest neighbor measure. They have been integrated within XmdvTool, a public-domain multiresolution visualization system for multivariate data analysis that supports sampling as well as clustering to simplify data. Several interactive operations are provided, including adjusting the data abstraction level, changing selected regions, and setting the acceptable data abstraction quality level. Conducting these operations, analysts can select an optimal data abstraction level. Also, analysts can compare different abstraction methods using the measures to see how well relative data density and outliers are maintained, and then select an abstraction method that meets the requirement of their analytic tasks
Multi-Scale Banking to 45 Degrees
Authors: Jeffrey Heer, Maneesh Agrawala
Published at InfoVis, 2006

In his text Visualizing Data, William Cleveland demonstrates how the aspect ratio of a line chart can affect an analyst's perception of trends in the data. Cleveland proposes an optimization technique for computing the aspect ratio such that the average absolute orientation of line segments in the chart is equal to 45 degrees. This technique, called banking to 45deg, is designed to maximize the discriminability of the orientations of the line segments in the chart. In this paper, we revisit this classic result and describe two new extensions. First, we propose alternate optimization criteria designed to further improve the visual perception of line segment orientations. Second, we develop multi-scale banking, a technique that combines spectral analysis with banking to 45deg. Our technique automatically identifies trends at various frequency scales and then generates a banked chart for each of these scales. We demonstrate the utility of our techniques in a range of visualization tools and analysis examples