DevLan/vispubs huggingface dataset:
RankSpiral: Toward Enhancing Search Results Visualizations
Authors: Anselm Spoerri
Published at InfoVis, 2004

This paper addresses the problem of how to enable users to visually explore and compare large sets of documents that have been retrieved by different search engines or queries. The Rank-Spiral enables users to rapidly scan large numbers of documents and their titles in a single screen. It uses a spiral mapping that maximizes information density and minimizes occlusions. It solves the labeling problem by exploiting the structure of the special spiral mapping used. Focus+Context interactions enable users to examine document clusters or groupings in more detail.
RecMap: Rectangular Map Approximations
Authors: Roland Heilmann, Daniel A. Keim, Christian Panse, Mike Sips
Published at InfoVis, 2004

In many application domains, data is collected and referenced by its geospatial location. Nowadays, different kinds of maps are used to emphasize the spatial distribution of one or more geospatial attributes. The nature of geospatial statistical data is the highly nonuniform distribution in the real world data sets. This has several impacts on the resulting map visualizations. Classical area maps tend to highlight patterns in large areas, which may, however, be of low importance. Cartographers and geographers used cartograms or value-by-area maps to address this problem long before computers were available. Although many automatic techniques have been developed, most of the value-by-area cartograms are generated manually via human interaction. In this paper, we propose a novel visualization technique for geospatial data sets called RecMap. Our technique approximates a rectangular partition of the (rectangular) display area into a number of map regions preserving important geospatial constraints. It is a fully automatic technique with explicit user control over all exploration constraints within the exploration process. Experiments show that our technique produces visualizations of geospatial data sets, which enhance the discovery of global and local correlations, and demonstrate its performance in a variety of applications
Resource Systems Reference Database
Authors: David Lu, Lauren Dietrich
Published at InfoVis, 2004

This interactive poster proposes a novel, explorative way to browse a database containing links to resource systems-related information online. Our approach is an illustrative one, and draws on our combined backgrounds in computer science, graphic and interaction design, sustainability, community organization, and urban design. The data visualized in our prototype was collected by students in the course Sustainable Habits, which Lauren Dietrich taught at Stanford University during Winter 2004.
Rethinking Visualization: A High-Level Taxonomy
Authors: Melanie Tory, Torsten Möller
Published at InfoVis, 2004

We present the novel high-level visualization taxonomy. Our taxonomy classifies visualization algorithms rather than data. Algorithms are categorized based on the assumptions they make about the data being visualized; we call this set of assumptions the design model. Because our taxonomy is based on design models, it is more flexible than existing taxonomies and considers the user's conceptual model, emphasizing the human aspect of visualization. Design models are classified according to whether they are discrete or continuous and by how much the algorithm designer chooses display attributes such as spatialization, timing, colour, and transparency. This novel approach provides an alternative view of the visualization field that helps explain how traditional divisions (e.g., information and scientific visualization) relates and overlap, and that may inspire research ideas in hybrid visualization areas
Steerable, Progressive Multidimensional Scaling
Authors: Matt Williams, Tamara Munzner
Published at InfoVis, 2004

Current implementations of multidimensional scaling (MDS), an approach that attempts to best represent data point similarity in a low-dimensional representation, are not suited for many of today's large-scale datasets. We propose an extension to the spring model approach that allows the user to interactively explore datasets that are far beyond the scale of previous implementations of MDS. We present MDSteer, a steerable MDS computation engine and visualization tool that progressively computes an MDS layout and handles datasets of over one million points. Our technique employs hierarchical data structures and progressive layouts to allow the user to steer the computation of the algorithm to the interesting areas of the dataset. The algorithm iteratively alternates between a layout stage in which a subselection of points are added to the set of active points affected by the MDS iteration, and a binning stage which increases the depth of the bin hierarchy and organizes the currently unplaced points into separate spatial regions. This binning strategy allows the user to select onscreen regions of the layout to focus the MDS computation into the areas of the dataset that are assigned to the selected bins. We show both real and common synthetic benchmark datasets with dimensionalities ranging from 3 to 300 and cardinalities of over one million points
TextPool: Visualizing Live Text Streams
Authors: Conrad Albrecht-Buehler, Benjamin Watson 0001, David A. Shamma
Published at InfoVis, 2004

In today's fast-paced world it is becoming increasingly difficult to stay abreast of the public discourse. With the advent of hundreds of closed-captioned cable channels and internet-based channels such as news feeds, blogs, or email, knowing the "buzz" is a particular challenge. TextPool addresses this problem by quickly summarizing recent content in live text streams. The summarization is a dynamically changing textual collage that clusters related terms. We tested TextPool with the content of several RSS newswire feeds, which are updated roughly every five minutes. TextPool was able to handle this bandwidth well, and produced useful summarizations of feed content.
The InfoVis Toolkit
Authors: Jean-Daniel Fekete
Published at InfoVis, 2004

This article presents the InfoVis toolkit, designed to support the creation, extension and integration of advanced 2D information visualization components into interactive Java swing applications. The InfoVis toolkit provides specific data structures to achieve a fast action/feedback loop required by dynamic queries. It comes with a large set of components such as range sliders and tailored control panels required to control and configure the visualizations. These components are integrated into a coherent framework that simplifies the management of rich data structures and the design and extension of visualizations. Supported data structures currently include tables, trees and graphs. Supported visualizations include scatter plots, time series, parallel coordinates, treemaps, icicle trees, node-link diagrams for trees and graphs and adjacency matrices for graphs. All visualizations can use fisheye lenses and dynamic labeling. The InfoVis toolkit supports hardware acceleration when available through Agile2D, an implementation of the Java graphics API based on OpenGL, achieving speedups of 10 to 200 times. The article also shows how new visualizations can be added and extended to become components, enriching visualizations as well as general applications
Time-Varying Data Visualization Using Information Flocking Boids
Authors: Andrew Vande Moere
Published at InfoVis, 2004

This research demonstrates how principles of self-organization and behavior simulation can be used to represent dynamic data evolutions by extending the concept of information flocking, originally introduced by Proctor &amp;amp; Winter (1998), to time-varying datasets. A rule-based behavior system continuously controls and updates the dynamic actions of individual, three-dimensional elements that represent the changing data values of reoccurring data objects. As a result, different distinguishable motion types emerge that are driven by local interactions between the spatial elements as well as the evolution of time-varying data values. Notably, this representation technique focuses on the representation of dynamic data alteration characteristics, or how reoccurring data objects change over time, instead of depicting the exact data values themselves. In addition, it demonstrates the potential of motion as a useful information visualization cue. The original information flocking approach is extended to incorporate time-varying datasets, live database querying, continuous data streaming, real-time data similarity evaluation, automatic shape generation and more stable flocking algorithms. Different experiments prove that information flocking is capable of representing short-term events as well as long-term temporal data evolutions of both individual and groups of time-dependent data objects. An historical stock market quote price dataset is used to demonstrate the algorithms and principles of time-varying information flocking
Topological Fisheye Views for Visualizing Large Graphs
Authors: Emden R. Gansner, Yehuda Koren, Stephen C. North
Published at InfoVis, 2004

Graph drawing is a basic visualization tool. For graphs of up to hundreds of nodes and edges, there are many effective techniques available. At greater scale, data density and occlusion problems often negate its effectiveness. Conventional pan-and-zoom, and multiscale and geometric fisheye views are not fully satisfactory solutions to this problem. As an alternative, we describe a topological zooming method. It is based on the precomputation of a hierarchy of coarsened graphs, which are combined on the fly into renderings with the level of detail dependent on the distance from one or more foci. We also discuss a related distortion method that allows our technique to achieve constant information density displays
Tracking User Interactions Within Visualizations
Authors: Dennis P. Groth, Benjamin W. Murphy
Published at InfoVis, 2004

We present a model and prototype system for tracking user interactions within a visualization. The history of the interactions are exposed to the user in a way that supports non-linear navigation of the visualization space. The interactions can be augmented with annotations, which, together with the interactions, can be shared with other users and applied to other data in a seamless way. The techniques constitute a novel approach for documenting information provenance.
Uncovering Clusters in Crowded Parallel Coordinates Visualizations
Authors: Almir Olivette Artero, Maria Cristina Ferreira de Oliveira, Haim Levkowitz
Published at InfoVis, 2004

The one-to-one strategy of mapping each single data item into a graphical marker adopted in many visualization techniques has limited usefulness when the number of records and/or the dimensionality of the data set are very high. In this situation, the strong overlapping of graphical markers severely hampers the user's ability to identify patterns in the data from its visual representation. We tackle this problem here with a strategy that computes frequency or density information from the data set, and uses such information in parallel coordinates visualizations to filter out the information to be presented to the user, thus reducing visual clutter and allowing the analyst to observe relevant patterns in the data. The algorithms to construct such visualizations, and the interaction mechanisms supported, inspired by traditional image processing techniques such as grayscale manipulation and thresholding are also presented. We also illustrate how such algorithms can assist users to effectively identify clusters in very noisy large data sets
Understanding Eight Years of InfoVis Conferences Using PaperLens
Authors: Bongshin Lee, Mary Czerwinski, George G. Robertson, Benjamin B. Bederson
Published at InfoVis, 2004

We present PaperLens, a visualization that reveals connections, trends, and activity throughout the InfoVis conference community for the last 8 years. It tightly couples views across papers, authors, and references. This paper describes how we analyzed the data, the strengths and weaknesses of PaperLens, and interesting patterns and relationships we have discovered using PaperLens.
User Experiments with Tree Visualization Systems
Authors: Alfred Kobsa
Published at InfoVis, 2004

This paper describes a comparative experiment with five well-known tree visualization systems, and Windows Explorer as a baseline system. Subjects performed tasks relating to the structure of a directory hierarchy, and to attributes of files and directories. Task completion times, correctness and user satisfaction were measured, and video recordings of subjects' interaction with the systems were made. Significant system and task type effects and an interaction between system and task type were found. Qualitative analyses of the video recordings were thereupon conducted to determine reasons for the observed differences, resulting in several findings and design recommendations as well as implications for future experiments with tree visualization systems
Value and Relation Display for Interactive Exploration of High Dimensional Datasets
Authors: Jing Yang 0001, Anilkumar Patro, Shiping Huang, Nishant K. Mehta, Matthew O. Ward, Elke A. Rundensteiner
Published at InfoVis, 2004

Traditional multidimensional visualization techniques, such as glyphs, parallel coordinates and scatterplot matrices, suffer from clutter at the display level and difficult user navigation among dimensions when visualizing high dimensional datasets. In this paper, we propose a new multidimensional visualization technique named a value and relation (VaR) display, together with a rich set of navigation and selection tools, for interactive exploration of datasets with up to hundreds of dimensions. By explicitly conveying the relationships among the dimensions of a high dimensional dataset, the VaR display helps users grasp the associations among dimensions. By using pixel-oriented techniques to present values of the data items in a condensed manner, the VaR display reveals data patterns in the dataset using as little screen space as possible. The navigation and selection tools enable users to interactively reduce clutter, navigate within the dimension space, and examine data value details within context effectively and efficiently. The VaR display scales well to datasets with large numbers of data items by employing sampling and texture mapping. A case study on a real dataset, as well as the VaR displays of multiple real datasets throughout the paper, reveals how our proposed approach helps users interactively explore high dimensional datasets with large numbers of data items
VIM: A Framework for Intelligence Analysis
Authors: Alan Keahey, Kenneth C. Cox
Published at InfoVis, 2004

Intelligence analysts receive thousands of facts from a variety of sources. In addition to the bare details of the fact — a particular person, for example — each fact may have provenance, reliability, weight, and other attributes. Each fact may also be associated with other facts, e.g. that one person met another at a particular location. The analyst’s task is to examine a huge collection of such loosely-structured facts, and try to "connect the dots" to perceive the underlying and unknown causes — and their possible future courses. We have designed and implemented a Java platform called VIM to support intelligence analysts in their work.
Visual Browsing of Remote and Distributed Data
Authors: Parthasarathy Krishnaswamy, Stephen G. Eick, Robert L. Grossman
Published at InfoVis, 2004

Data repositories around the world hold many thousands of data sets. Finding information from these data sets is greatly facilitated by being able to quickly and efficiently browse remote data sets. In this note, we introduce the Iconic Remote Visual Data Exploration tool(IRVDX), which is a visual data mining tool used for exploring the features of remote and distributed data without the necessity of downloading the entire data set. IRVDX employs three kinds of visualizations: one provides a reduced representation of the data sets, which we call Dataset Icons. These icons show the important statistical characteristics of data sets and help to identify relevant data sets from distributed repositories. Another one is called the Remote Dataset Visual Browser that provides visualizations to browse remote data without downloading the complete data set to identify its content. The final one provides visualizations to show the degree of similarity between two data sets and to visually determine whether a join of two remote data sets will be meaningful.
Visualizing and Interacting with Multi-Tree Hierarchical Data
Authors: Mahnas Jean Mohammadi-Aragh, T. J. Jankun-Kelly
Published at InfoVis, 2004

This work focuses on visualizing highly cyclic hierarchical data. A user interface is discussed and its interaction is illustrated using a recipe database example. This example showcases a database with multiple categories for each recipe (database entry).
Visualizing E-mail with a Semantically Zoomable Interface
Authors: Ellen Diep, Robert J. K. Jacob
Published at InfoVis, 2004

We introduce a semantically zoomable interface that displays emails as interactive objects rather than files containing lines of text, as in traditional e-mail interfaces. In this system, e-mails are displayed as node objects called e-mail nodes within a 2.5-dimensional world. The e-mail nodes are semantically zoomable and each may be rearranged to different locations within the plane to organize threads, topics, or projects. The prototype for this system was built using the Piccolo toolkit, the successor of Pad++ and Jazz [2, 3].
Visualizing High Dimensional Datasets Using Partiview
Authors: Dinoj Surendran, Stuart Levy
Published at InfoVis, 2004

A standard method of visualizing high-dimensional data is reducing its dimensionality to two or three using some algorithm, and then creating a scatterplot with data represented by labelled and/or colored dots. Two problems with this approach are (1) dots do not represent data well, (2) reducing to just three dimensions does not make full use of several dimensionality-reduction algorithms. We demonstrate how Partiview can be used to solve these problems, in the context of handwriting recognition and image retrieval.
WilmaScope Graph Visualisation
Authors: Adel Ahmed, Tim Dwyer, Colin Murray, Le Song, Ying Xin Wu
Published at InfoVis, 2004

Our visualisation of the IEEE InfoVis citation network is based on 3D graph visualisation techniques. To make effective use of the third dimension we use a layered approach, constraining nodes to lie on parallel planes depending on parameters such as year of publication or link degree. Within the parallel planes nodes are arranged using a fast force-directed layout method. A number of clusters representing different research areas were identified using a self organising map approach.
A Botanically Inspired High-Dimensional Visualization with Multivariate Glyphs
Authors: Eleanor Boyle Chlan, Penny Rheingans
Published at EuroVis, 2004

It is difficult for the average viewer to assimilate and comprehend huge amounts of high-dimensional data. It is important to present data in a way that allows the user a high level understanding of the overall organization and structure without losing the ability to study low level detail as needed. Although hierarchically clustered data is already organized, many current means of presenting such data give the user little more than an overview of the organization. It would be useful to see more information about the data even at a high level and to examine specific clusters as needed. We want to understand the relationships of the clusters in terms of the underlying data, and to understand the extent and variability of the data without requiring examination of each data item. To meet these goals, we present an aesthetically appealing visualization based on botanical trees which preserves the natural order of hierarchically organized data. Hierarchical data is rendered as a simple branched tree. The tree gives an overview of the relationships among various clusters and is supplemented with two glyphs which allow the user to focus in on specific clusters of the data at different levels of detail. At a medium level of focus, a cluster glyph based on a radial, space filling approach shows the subtree rooted at a specified cluster. At a low level of detail, the branch glyph allows the viewer to see not only aggregate information about the cluster but the extent and variability of the component clusters.
A Cluster-Space Visual Interface for Arbitrary Dimensional Classification of Volume Data
Authors: Fan-Yin Tzeng, Kwan-Liu Ma
Published at EuroVis, 2004

In volume visualization, users typically specify transfer functions to classify the data and assign visual attributes to each material class. Higher-dimensional classification makes it easier to differentiate material classes since more data properties are considered. One of the difficulties in using higher-dimensional classification is the absence of appropriate user interfaces. We introduce an intuitive user interface that allows the user to work in the cluster space, which shows the material classes with a set of material widgets, rather than work in the transfer function space. This interface not only provides the user the capability to specify arbitrary-dimensional transfer functions, but also allows the user to operate directly on the classification and visualization results.
Accuracy Evaluation of Different Centerline Approximations of Blood Vessels
Authors: Alexandra La Cruz
Published at EuroVis, 2004

Accurate determination of the vessel axis is a prerequisite for automated visualization and quantification of artery diseases. This paper presents an evaluation of different methods for approximating the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting using thresholds and maximum gradient-like stop criterion, pixel motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting have been used as shape based segmentation techniques. Since in the synthetic data set the centerline is known, an estimation of the error can be calculated in order to determine the accuracy achieved by a given method.
Adaptive Volume Construction from Ultrasound Images of a Human Heart
Authors: Gerd Reis, Martin Bertram 0001, Rolf Hendrik van Lengen, Hans Hagen
Published at EuroVis, 2004

We present a volume modelling approach based on sequences of two-dimensional ultrasound images. Though generally applicable to arbitrary freehand ultrasound, our method is designed for the reconstruction of timevarying volumes from ultrasound images of a human heart. Since the reliability of the reconstructed data depends very much on the spatial density of ultrasound images, we apply a hierarchical modelling approach. The volume produced for each time step is represented as adaptive mesh refinement (AMR) data such that regions of low reliability in the reconstructed volume can be recognized by their coarse resolution.
Auralization I: Vortex Sound Synthesis
Authors: Youngin Shin, Chandrajit L. Bajaj
Published at EuroVis, 2004

Auralization is the process of extracting and displaying meaningful information in the form of sound from data. Through not only visualization but also auralization, users may have better understandings of the data, especially when it is visually complicated. In this work, a field auralization technique is introduced, which objective is at the sound synthesis from field information represented as 3D time-varying volume data. Our technique takes a hybrid approach between parameter mapping and direct simulation. During preprocessing, acoustic strengths are computed at each vertex at each time step of volume data. During interaction, users navigate within the volume space and audio frames are computed by integrating the radiations from the sources. A number of problems inherent in this problem and our solutions are discussed.