DevLan/vispubs huggingface dataset:
Coordinated graph and scatter-plot views for the visual exploration of microarray time-series data
Authors: Paul Craig, Jessie Kennedy
Published at InfoVis, 2003

Microarrays are relatively new, high-throughput data acquisition technology for investigating biological phenomena at the micro-level. One of the more common procedures for microarray experimentation is that of the microarray time-course experiment. The product of microarray time-course experiment is time-series data, which subject to proper analysis has the potential to have significant impact on the diagnosis, treatment, and prevention of diseases. While existing information visualization techniques go some way to making microarray time-series data more manageable, requirements analysis has revealed significant limitations. The main finding was that users were unable to uncover and quantify common changes in value over a specified time-period. This paper describes a novel technique that provides this functionality by allowing the user to visually formulate and modify measurable queries with separate time-period and condition components. These visual queries are supported by the combination of a traditional value against time graph representation of the data with a complementary scatter-plot representation of a specified time-period. The multiple views of the visualization are coordinated so that the user can formulate and modify queries with rapid reversible display of query results in the traditional value against time graph format.
Design choices when architecting visualizations
Authors: Diane Tang, Chris Stolte, Robert P. Bosch Jr.
Published at InfoVis, 2003

In this paper, we focus on some of the key design decisions we faced during the process of architecting a visualization system and present some possible choices, with their associated advantages and disadvantages. We frame this discussion within the context of Rivet, our general visualization environment designed for rapidly prototyping interactive, exploratory visualization tools for analysis. As we designed increasingly sophisticated visualizations, we needed to refine Rivet in order to be able to create these richer displays for larger and more complex data sets. The design decisions we discuss in this paper include: the internal data model, data access, semantic meta-data information the visualization can use to create effective visual decodings, the need for data transformations in a visualization tool, modular objects for flexibility, and the tradeoff between simplicity and expressiveness when providing methods for creating visualizations.
Developing architectural lighting representations
Authors: Daniel C. Glaser, Roger Tan, John F. Canny, Ellen Yi-Luen Do
Published at InfoVis, 2003

This paper reports on the development of a visualization system for architectural lighting designers. It starts by motivating the problem as both complex in its physics and social organization. Three iterations of prototypes for displaying time and space varying phenomena are discussed. Fieldwork is presented to identify where in practice they will be most effective. A set of user studies, one of which is analyzed in fine-grained detail, show how building designers incorporate visualization on hypothetical design problems. This has positive implications for both energy efficiency and lighting quality in buildings.
Dynamic visualization of transient data streams
Authors: Pak Chung Wong, Harlan Foote, Dan Adams, Wendy Cowley, James J. Thomas
Published at InfoVis, 2003

We introduce two dynamic visualization techniques using multidimensional scaling to analyze transient data streams such as newswires and remote sensing imagery. While the time-sensitive nature of these data streams requires immediate attention in many applications, the unpredictable and unbounded characteristics of this information can potentially overwhelm many scaling algorithms that require a full re-computation for every update. We present an adaptive visualization technique based on data stratification to ingest stream information adaptively when influx rate exceeds processing rate. We also describe an incremental visualization technique based on data fusion to project new information directly onto a visualization subspace spanned by the singular vectors of the previously processed neighboring data. The ultimate goal is to leverage the value of legacy and new information and minimize re-processing of the entire dataset in full resolution. We demonstrate these dynamic visualization results using a newswire corpus and a remote sensing imagery sequence.
Edgelens: an interactive method for managing edge congestion in graphs
Authors: Nelson Wong, Sheelagh Carpendale, Saul Greenberg
Published at InfoVis, 2003

An increasing number of tasks require people to explore, navigate and search extremely complex data sets visualized as graphs. Examples include electrical and telecommunication networks, Web structures, and airline routes. The problem is that graphs of these real world data sets have many interconnected nodes, ultimately leading to edge congestion: the density of edges is so great that they obscure nodes, individual edges, and even the visual information beneath the graph. To address this problem we developed an interactive technique called EdgeLens. An EdgeLens interactively curves graph edges away for a person's focus attention without changing the node positions. This opens up sufficient space to disambiguate node and edge relationships and to see underlying information while still preserving node layout. Initially two methods of creating this interaction were developed and compared in a user study. The results of this study were used in the selection of a basic approach and the subsequent development of the EdgeLens. We then improved the EdgeLens through use of transparency and colour and by allowing multiple lenses to appear on the graph.
Empirical comparison of dynamic query sliders and brushing histograms
Authors: Qing Li, Chris North 0001
Published at InfoVis, 2003

Dynamic queries facilitate rapid exploration of information by real-time visual display of both query formulation and results. Dynamic query sliders are linked to the main visualization to filter data. A common alternative to dynamic queries is to link several simple visualizations, such as histograms, to the main visualization with a brushing interaction strategy. Selecting data in the histograms highlights that data in the main visualization. We compare these two approaches in an empirical experiment on DataMaps, a geographic data visualization tool. Dynamic query sliders resulted in better performance for simple range tasks, while brushing histograms was better for complex trend evaluation and attribute relation tasks. Participants preferred brushing histograms for understanding relationships between attributes and the rich information they provided.
Exploding the frame: designing for wall-size computer displays
Authors: Ben Shedd
Published at InfoVis, 2003

High-resolution wall-size digital displays present significant new and different visual space to show and see imagery. The author has been working with two wall-size digital displays at Princeton University for five years and directing and producing IMAX films for a decade, and he has noted some unique design considerations for creating effective visual images when they are spread across entire walls. The author suggests these "frameless" screens - where images are so large we need to look around to see the entire field - need different ways of thinking about image design and visualization. Presenting such things as scale and detail take on new meaning when they can be displayed life-size and not shown in the context of one or many small frames such as we see everywhere. These design ideas will be of use for pervasive computing, interface research and design, interactive design, control design, representations of massive data sets, and creating effective displays of data for research and education.
Exploring high-D spaces with multiform matrices and small multiples
Authors: Alan M. MacEachren, Xiping Dai, Frank Hardisty, Diansheng Guo, Eugene Lengerich
Published at InfoVis, 2003

We introduce an approach to visual analysis of multivariate data that integrates several methods from information visualization, exploratory data analysis (EDA), and geovisualization. The approach leverages the component-based architecture implemented in GeoVISTA Studio to construct a flexible, multiview, tightly (but generically) coordinated, EDA toolkit. This toolkit builds upon traditional ideas behind both small multiples and scatterplot matrices in three fundamental ways. First, we develop a general, multiform, bivariate matrix and a complementary multiform, bivariate small multiple plot in which different bivariate representation forms can be used in combination. We demonstrate the flexibility of this approach with matrices and small multiples that depict multivariate data through combinations of: scatterplots, bivariate maps, and space-filling displays. Second, we apply a measure of conditional entropy to (a) identify variables from a high-dimensional data set that are likely to display interesting relationships and (b) generate a default order of these variables in the matrix or small multiple display. Third, we add conditioning, a kind of dynamic query/filtering in which supplementary (undisplayed) variables are used to constrain the view onto variables that are displayed. Conditioning allows the effects of one or more well understood variables to be removed form the analysis, making relationships among remaining variables easier to explore. We illustrate the individual and combined functionality enabled by this approach through application to analysis of cancer diagnosis and mortality data and their associated covariates and risk factors.
FundExplorer: supporting the diversification of mutual fund portfolios using context treemaps
Authors: Christoph Csallner, Marcus Handte, Othmar Lehmann, John T. Stasko
Published at InfoVis, 2003

An equity mutual fund is a financial instrument that invests in a set of stocks. Any two different funds may partially invest in some of the same stocks, thus overlap is common. Portfolio diversification aims at spreading an investment over many different stocks in search of greater returns. Helping people with portfolio diversification is challenging because it requires informing them about both their current portfolio of stocks held through funds and the other stocks in the market not invested in yet. Current stock/fund visualization systems either waste screen real estate and visualization of all data points. We have developed a system called FundExplorer that implements a distorted treemap to visualize both the amount of money invested in a person's fund portfolio and the context of remaining market stocks. The FundExplorer system enables people to interactively explore diversification possibilities with their portfolios.
IEEE Symposium on Information Visualization 2003 (IEEE Cat. No.03TH8714)
Authors: Tamara Munzner, Steven C. North
Published at InfoVis, 2003

The following topics are dealt with: computer displays; multiscaling; graphs; high dimensionality; occlusion; visualization evaluation; linking and design studies.
Improving Hybrid MDS with Pivot-Based Searching
Authors: Alistair Morrison, Matthew Chalmers
Published at InfoVis, 2003

An algorithm is presented for the visualization of multidimensional abstract data, building on a hybrid model introduced at Info Vis 2002. The most computationally complex stage of the original model involved performing a nearest-neighbour search for every data item. The complexity of this phase has been reduced by treating all high-dimensional relationships as a set of discretised distances to a constant number of randomly selected pivot items. In improving this computational bottleneck, the complexity is reduced to from O(N/sub 1/2 /N) to O(N/sub 5/4/). As well as documenting this improvement, the paper describes evaluation with a data set of 108000 14-dimensional items; a considerable increase on the size of data previously tested. Results illustrate that the reduction in complexity is reflected in significantly improved run times and that no negative impact is made upon the quality of layout produced.
Information esthetics: from MoMa to wall street
Authors: W. Bradford Paley
Published at InfoVis, 2003

My after-dinner talk has the goal of being a visual dessert, showing some of the information designs and explorations that I've put together in the last twenty years as a practicing designer and more recently, as an artist. I'll show the ones that people reacted to most strongly; partly to soothe and entertain, but partly in the hopes that some of the techniques I apply might be useful in the work of other attendees.

To that end I'll present a simplified Knowledge Acquisition Pipeline, a kind of designer's checklist that has been valuable in guiding my students and me while creating information-rich displays and user interfaces. It helps organize the wide variety of techniques available to us as information designers. But more--it helps us understand why they might work, where they might be useful in a design, and even what types of information can best be shown with which techniques. It works as a generative guideline as well as an intellectual framework. I'll tie parts of the examples back to this pipeline to show how it works in practice.

The application of this pipeline to visualization work suggests that as a field we are getting good value out of our understanding of the earlier processes--those having to do with sensation and perception. But later processes still have a lot of room for exploration: the visual attributes we use to represent data can often be made more specific, and therefore both more communicative and easier to decode. The world is richer than we can describe with circular nodes and linear links. And when we can get a visual vocabulary from the target audience, their own higher level semantic relationships may also be more easily absorbed and manipulated. I suggest that what such "illustrative information displays" lose in generality they more than make up in ease of interpretation and viewer engagement.
Intelligently resolving point occlusion
Authors: Marjan Trutschl, Georges G. Grinstein, Urska Cvek
Published at InfoVis, 2003

Large and high-dimensional data sets mapped to low-dimensional visualizations often result in perceptual ambiguities. One such ambiguity is overlap or occlusion that occurs when the number of records exceeds the number of unique locations in the presentation or when there exist two or more records that map to the same location. To lessen the affect of occlusion, non-standard visual attributes (i.e. shading and/or transparency) are applied, or such records may be remapped to a corresponding jittered location. The resulting mapping efficiently portrays the crowding of records but fails to provide the insight into the relationship between the neighboring records. We introduce a new interactive technique that intelligibly organizes overlapped points, a neural network-based smart jittering algorithm. We demonstrate this technique on a scatter plot, the most widely used visualization. The algorithm can be applied to other one, two, and multi-dimensional visualizations which represent data as points, including 3-dimensional scatter plots, RadViz, polar coordinates.
Interactive hierarchical dimension ordering, spacing and filtering for exploration of high dimensional datasets
Authors: Jing Yang 0001, Wei Peng, Matthew O. Ward, Elke A. Rundensteiner
Published at InfoVis, 2003

Large number of dimensions not only cause clutter in multi-dimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension management, such as dimension ordering, spacing and filtering, is critical for visual exploration of such datasets. Dimension ordering and spacing explicitly reveal dimension relationships in arrangement-sensitive multidimensional visualization techniques, such as parallel coordinates, star glyphs, and pixel-oriented techniques. They facilitate the visual discovery of patterns within the data. Dimension filtering hides some of the dimensions to reduce clutter while preserving the major information of the dataset. In this paper, we propose an interactive hierarchical dimension ordering, spacing and filtering approach, called DOSFA. DOSFA is based on dimension hierarchies derived from similarities among dimensions. It is scalable multi-resolution approach making dimensional management a tractable task. On the one hand, it automatically generates default settings for dimension ordering, spacing and filtering. On the other hand, it allows users to efficiently control all aspects of this dimension management process via visual interaction tools for dimension hierarchy manipulation. A case study visualizing a dataset containing over 200 dimensions reveals high dimensional visualization techniques.
Mapping nominal values to numbers for effective visualization
Authors: Geraldine E. Rosario, Elke A. Rundensteiner, David C. Brown, Matthew O. Ward
Published at InfoVis, 2003

Data sets with a large number of nominal variables, some with high cardinality, are becoming increasingly common and need to be explored. Unfortunately, most existing visual exploration displays are designed to handle numeric variables only. When importing data sets with nominal values into such visualization tools, most solutions to date are rather simplistic. Often, techniques that map nominal values to numbers do not assign order or spacing among the values in a manner that conveys semantic relationships. Moreover, displays designed for nominal variables usually cannot handle high cardinality variables well. This paper addresses the problem of how to display nominal variables in general-purpose visual exploration tools designed for numeric variables. Specifically, we investigate (1) how to assign order and spacing among the nominal values, and (2) how to reduce the number of distinct values to display. We propose that nominal variables be pre-processed using a distance-quantification-classing (DQC) approach before being imported into a visual exploration tool. In the distance step, we identify a set of independent dimensions that can be used to calculate the distance between nominal values. In the quantification step, we use the independent dimensions and the distance information to assign order and spacing among the nominal values. In the classing step, we use results from the previous steps to determine which values within a variable are similar to each other and thus can be grouped together. Each step in the DQC approach can be accomplished by a variety of techniques. We extended the XmdvTool package to incorporate this approach. We evaluated our approach on several data sets using a variety of evaluation measures.
MoireGraphs: radial focus+context visualization and interaction for graphs with visual nodes
Authors: T. J. Jankun-Kelly, Kwan-Liu Ma
Published at InfoVis, 2003

Graph and tree visualization techniques enable interactive exploration of complex relations while communicating topology. However, most existing techniques have not been designed for situations where visual information such as images is also present at each node and must be displayed. This paper presents MoireGraphs to address this need. MoireGraphs combine a new focus+context radial graph layout with a suite of interaction techniques (focus strength changing, radial rotation, level highlighting, secondary foci, animated transitions and node information) to assist in the exploration of graphs with visual nodes. The method is scalable to hundreds of displayed visual nodes.
Multiscale Visualization of Small World Networks
Authors: David Auber, Yves Chiricota, Fabien Jourdan, Guy Melançon
Published at InfoVis, 2003

Many networks under study in information visualization are "small world" networks. These networks first appeared in the study of social networks and were shown to be relevant models in other application domains such as software reverse engineering and biology. Furthermore, many of these networks actually have a multiscale nature: they can be viewed as a network of groups that are themselves small world networks. We describe a metric that has been designed in order to identify the weakest edges in a small world network leading to an easy and low cost filtering procedure that breaks up a graph into smaller and highly connected components. We show how this metric can be exploited through an interactive navigation of the network based on semantic zooming. Once the network is decomposed into a hierarchy of sub-networks, a user can easily find groups and subgroups of actors and understand their dynamics.
Smooth and efficient zooming and panning
Authors: Jarke J. van Wijk, Wim A. A. Nuij
Published at InfoVis, 2003

Large 2D information spaces, such as maps, images, or abstract visualizations, require views at various level of detail: close ups to inspect details, overviews to maintain (literally) an overview. Users often switch between these views. We discuss how smooth animations from one view to another can be defined. To this end, a metric on the effect of simultaneous zooming and panning is defined, based on an estimate of the perceived velocity. Optimal is defined as smooth and efficient. Given the metric, these terms can be translated into a computational model, which is used to calculate an analytic solution for optimal animations. The model has two free parameters: animation speed and zoom/pan trade off. A user experiment to find good values for these is described.
Thinking with visualization
Authors: Colin Ware
Published at InfoVis, 2003

Visualizations help us to solve problems by finding patterns in graphical displays of data. For example, finding a pattern of highly connected components in a node link diagram can help us understand the architecture of a software system. Finding a long, red, fairly straight line on a map can show us the best way of driving between two cities. This talk will describe how thinking with visualizations involves the construction of visual queries on the display. Once a visual query is constructed, a visual search strategy through eye movements and attention to relevant patterns provides answers. Recent results from cognitive psychology can help us understand the visual thinking process. I will show how understanding the nature of visual queries, and the capacity of visual working memory, can be used to predict which visual tasks will be easy and which will be difficult, if not impossible. Examples from common visualizations and interactive techniques will be used to illustrate the central concepts.
Thread Arcs: an email thread visualization
Authors: Bernard Kerr
Published at InfoVis, 2003

This paper describes Thread Arcs, a novel interactive visualization technique designed to help people use threads found in email. Thread Arcs combine the chronology of messages with the branching tree structure of a conversational thread in a mixed-model visualization by Venolia and Neustaedter (2003) that is stable and compact. By quickly scanning and interacting with Thread Arcs, people can see various attributes of conversations and find relevant messages in them easily. We tested this technique against other visualization techniques with users' own email in a functional prototype email client. Thread Arcs proved an excellent match for the types of threads found in users' email for the qualities users wanted in small-scale visualizations.