DevLan/vispubs huggingface dataset:
Volume MLS Ray Casting
Authors: Christian Ledergerber, Gaël Guennebaud, Miriah D. Meyer, Moritz Bächer, Hanspeter Pfister
Published at Vis, 2008

The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-understood theoretical foundations. This paper applies MLS to volume rendering, providing a unified mathematical framework for ray casting of scalar data stored over regular as well as irregular grids. We use the MLS reconstruction to render smooth isosurfaces and to compute accurate derivatives for high-quality shading effects. We also present a novel, adaptive preintegration scheme to improve the efficiency of the ray casting algorithm by reducing the overall number of function evaluations, and an efficient implementation of our framework exploiting modern graphics hardware. The resulting system enables high-quality volume integration and shaded isosurface rendering for regular and irregular volume data.
A 3D treemap approach for analyzing the classificatory distribution in patent portfolios
Authors: Mark Giereth, Harald Bosch, Thomas Ertl
Published at VAST, 2008

Due to the complexity of the patent domain and the huge amount of data, advanced interactive visual techniques are needed to support the analysis of large patent collections and portfolios. In this paper we present a new approach for visualizing the classificatory distribution of patent collections among the International Patent Classification (IPC) - todaypsilas most important internationally agreed patent classification system with about 70.000 categories. Our approach is based on an interactive three-dimensional treemap overlaid with adjacency edge bundles.
A compound approach for interactive visualization of time-oriented data
Authors: Tim Lammarsch
Published at VAST, 2008

Many real-world visual analytics applications involve time-oriented data. I am working in a research project related to this challenge where I am responsible for the interactive visualization part. My goal are interactive visualizations to explore such time-oriented data according to the user tasks while considering the structure of time. Time is composed of many granularities that are likely to have crucial influence on the formation of the data. The challenge is to integrate the granularities into a detailed compound view on the data, like the compound eye of insects integrates many images into one view. Other members of our team are experts in temporal data mining and user centered design. The goal is to combine our research topics to an integrated system that helps domain experts to get more insight from their time-oriented data.
An information visualisation system for the understanding of web data
Authors: Victor Pascual-Cid
Published at VAST, 2008

Internet has become one of the best communication and marketing tools. Hence, designing well-structured Web sites with the information or products that users look for is a crucial mission. For this reason, understanding Web data is a decisive task to assure the success of a Website. In that sense, data mining techniques provide many metrics and statistics useful to automatically discover the structure, contents and usage of a site. This research aims at proving the usefulness of a set of information visualisation techniques in order to analyse Web data, using a visual Web mining tool that allows the combination, coordination and exploration of visualisations to get insight on Web data. The tool, named WET, provides a set of visual metaphors that represent the structure of the Websites where Web metrics are overlaid.
Applied visual analytics for economic decision-making
Authors: Anya Samak, Ross Maciejewski, David S. Ebert
Published at VAST, 2008

This paper introduces the application of visual analytics techniques as a novel approach for improving economic decision making. Particularly, we focus on two known problems where subjectspsila behavior consistently deviates from the optimal, the Winnerpsilas and Loserpsilas Curse. According to economists, subjects fail to recognize the profit-maximizing decision strategy in both the Winnerpsilas and Loserpsilas curse because they are unable to properly consider all the available information. As such, we have created a visual analytics tool to aid subjects in decision making under the Acquiring a Company framework common in many economic experiments. We demonstrate the added value of visual analytics in the decision making process through a series of user studies comparing standard visualization methods with interactive visual analytics techniques. Our work presents not only a basis for development and evaluation of economic visual analytic research, but also empirical evidence demonstrating the added value of applying visual analytics to general decision making tasks.
Award: Efficient toolkit integration solving the cell phone calls challenge with the Prajna Project
Authors: Edward Swing
Published at VAST, 2008

The Prajna Project is a Java toolkit designed to provide various capabilities for visualization, knowledge representation, geographic displays, semantic reasoning, and data fusion. Rather than attempt to recreate the significant capabilities provided in other tools, Prajna instead provides software bridges to incorporate other toolkits where appropriate. This challenge required the development of a custom application for visual analysis. By applying the utilities within the Prajna project, I developed a robust and diverse set of capabilities to solve the analytical challenge.
Cell phone mini challenge award: Intuitive social network graphs visual analytics of cell phone data using mobivis and ontovis
Authors: Carlos D. Correa, Tarik Crnovrsanin, Chris Muelder, Zeqian Shen, Ryan Armstrong, James Shearer, Kwan-Liu Ma
Published at VAST, 2008

MobiVis is a visual analytics tools to aid in the process of processing and understanding complex relational data, such as social networks. At the core of these tools is the ability to filter complex networks structurally and semantically, which helps us discover clusters and patterns in the organization of social networks. Semantic filtering is obtained via an ontology graph, based on another visual analytics tool, called OntoVis. In this summary, we describe how these tools where used to analyze one of the mini-challenges of the 2008 VAST challenge.
Cell phone mini challenge award: Social network accuracy - exploring temporal communication in mobile call graphs
Authors: Qi Ye, Tian Zhu 0001, Deyong Hu, Bin Wu 0001, Nan Du, Bai Wang 0001
Published at VAST, 2008

In the mobile call mini challenge of VAST 2008 contest, we explored the temporal communication patterns of Catalano/Vidro social network which is reflected in the mobile call data. We focus on detecting the hierarchy of the social network and try to get the important actors in it. We present our tools and methods in this summary. By using the visual analytic approaches, we can find out not only the temporal communication patterns in the social network but also the hierarchy of it.
Cell phone Mini Challenge: Node-link animation award animating multivariate dynamic social networks
Authors: Michael Farrugia, Aaron J. Quigley
Published at VAST, 2008

This article describes the visualization tool developed for analysing a dynamic social network of phone calls, for the VAST 2008 mini challenge. The tool was designed to highlight temporal changes in the network, by animating different network visual representations. We also explain how animating these network representations, helped to identify key events in the mini challenge problem scenario. Finally, we make some suggestions for future research and development in the area.
Characterizing users' visual analytic activity for insight provenance
Authors: David Gotz, Michelle X. Zhou
Published at VAST, 2008

Insight provenance - a historical record of the process and rationale by which an insight is derived - is an essential requirement in many visual analytics applications. While work in this area has relied on either manually recorded provenance (e.g., user notes) or automatically recorded event-based insight provenance (e.g., clicks, drags, and key-presses), both approaches have fundamental limitations. Our aim is to develop a new approach that combines the benefits of both approaches while avoiding their deficiencies. Toward this goal, we characterize userspsila visual analytic activity at multiple levels of granularity. Moreover, we identify a critical level of abstraction, Actions, that can be used to represent visual analytic activity with a set of general but semantically meaningful behavior types. In turn, the action types can be used as the semantic building blocks for insight provenance. We present a catalog of common actions identified through observations of several different visual analytic systems. In addition, we define a taxonomy to categorize actions into three major classes based on their semantic intent. The concept of actions has been integrated into our labpsilas prototype visual analytic system, HARVEST, as the basis for its insight provenance capabilities.
Collaborative synthesis of visual analytic results
Authors: Anthony C. Robinson
Published at VAST, 2008

Visual analytic tools allow analysts to generate large collections of useful analytical results. We anticipate that analysts in most real world situations will draw from these collections when working together to solve complicated problems. This indicates a need to understand how users synthesize multiple collections of results. This paper reports the results of collaborative synthesis experiments conducted with expert geographers and disease biologists. Ten participants were worked in pairs to complete a simulated real-world synthesis task using artifacts printed on cards on a large, paper-covered workspace. Experiment results indicate that groups use a number of different approaches to collaborative synthesis, and that they employ a variety of organizational metaphors to structure their information. It is further evident that establishing common ground and role assignment are critical aspects of collaborative synthesis. We conclude with a set of general design guidelines for collaborative synthesis support tools.
Configurable Spaces: Temporal analysis in diagrammatic contexts
Authors: Thomas Kapler, Ryan Eccles, Robert Harper 0002, William Wright
Published at VAST, 2008

Social network graphs, concept maps, and process charts are examples of diagrammatic representations employed by intelligence analysts to understand complex systems. Unfortunately, these 2D representations currently do not easily convey the flow, sequence, tempo and other important dynamic behaviors within these systems. In this paper we present Configurable Spaces, a novel analytical method for visualizing patterns of activity over time in complex diagrammatically- represented systems. Configurable Spaces extends GeoTime's X, Y, T coordinate workspace space for temporal analysis to any arbitrary diagrammatic work space by replacing a geographic map with a diagram. This paper traces progress from concept to prototype, and discusses how diagrams can be created, transformed and leveraged for analysis, including generating diagrams from knowledge bases, visualizing temporal concept maps, and the use of linked diagrams for exploring complex, multi-dimensional, sequences of events. An evaluation of the prototype by the National Institute of Standards and Technology showed intelligence analysts believed they were able to attain an increased level of insight, were able to explore data more efficiently, and that Configurable Spaces would help them work faster.
Crystal structures classifier for an evolutionary algorithm structure predictor
Authors: Mario Valle, Artem R. Oganov
Published at VAST, 2008

USPEX is a crystal structure predictor based on an evolutionary algorithm. Every USPEX run produces hundreds or thousands of crystal structures, some of which may be identical. To ease the extraction of unique and potentially interesting structures we applied usual high-dimensional classification concepts to the unusual field of crystallography. We experimented with various crystal structure descriptors, distinct distance measures and tried different clustering methods to identify groups of similar structures. These methods are already applied in combinatorial chemistry to organic molecules for a different goal and in somewhat different forms, but are not widely used for crystal structures classification. We adopted a visual design and validation method in the development of a library (CrystalFp) and an end-user application to select and validate method choices, to gain userspsila acceptance and to tap into their domain expertise. The use of the classifier has already accelerated the analysis of USPEX output by at least one order of magnitude, promoting some new crystallographic insight and discovery. Furthermore the visual display of key algorithm indicators has led to diverse, unexpected discoveries that will improve the USPEX algorithms.
Entity-based collaboration tools for intelligence analysis
Authors: Eric A. Bier, Stuart K. Card, John W. Bodnar
Published at VAST, 2008

Software tools that make it easier for analysts to collaborate as a natural part of their work will lead to better analysis that is informed by more perspectives. We are interested to know if software tools can be designed that support collaboration even as they allow analysts to find documents and organize information (including evidence, schemas, and hypotheses). We have modified the Entity Workspace system, described previously, to test such designs. We have evaluated the resulting design in both a laboratory study and a study where it is situated with an analysis team. In both cases, effects on collaboration appear to be positive. Key aspects of the design include an evidence notebook optimized for organizing entities (rather than text characters), information structures that can be collapsed and expanded, visualization of evidence that emphasizes events and documents (rather than emphasizing the entity graph), and a notification system that finds entities of mutual interest to multiple analysts.
Envisioning user models for adaptive visualization
Authors: Jae-wook Ahn, Peter Brusilovsky
Published at VAST, 2008

Adaptive search systems apply user models to provide better separation of relevant and non-relevant documents in a list of results. This paper presents our attempt to leverage this ability of user models in the context of visual information analysis. We developed an adaptive visualization approach for presentation and exploration of search results. We simulated a visual intelligence search/analysis scenario with log data extracted from an adaptive information foraging study and were able to verify that our method can improve the ability of traditional relevance visualization to separate relevant and irrelevant information.
Evacuation trace Mini Challenge award: Tool integration analysis of movements with Geospatial Visual Analytics Toolkit
Authors: Natalia V. Andrienko, Gennady L. Andrienko
Published at VAST, 2008

The Geospatial Visual Analytics Toolkit intended for exploratory analysis of spatial and spatio-temporal data has been recently enriched with specific visual and computational techniques supporting analysis of data about movement. We applied these and other techniques to the data and tasks of Mini Challenge 4, where it was necessary to analyze tracks of moving people.CR Categories and Subject Descriptors: H.1.2 [User/Machine Systems]: Human information processing - Visual Analytics; 1.6.9 [Visualization]: information visualization.
Evacuation Traces Mini Challenge award: Innovative trace visualization staining for information discovery
Authors: Dennis J. Bouvier, Britian Oates
Published at VAST, 2008

Staining is a technique for categorizing time-varying spatial data; that is, data of things moving through space over time. In Staining, a stain is applied in either time or space, and the objects which move through the stain become marked. This technique and a research prototype demonstrating the technique were developed in response to the VAST 2008 Contest Mini-challenge: Evacuation Traces.
Evacuation traces mini challenge: User testing to obtain consensus discovering the terrorist
Authors: Adalberto L. Simeone, Paolo Buono
Published at VAST, 2008

The adoption of visual analytics methodologies in security applications is an approach that could lead to interesting results. Usually, the data that has to be analyzed finds in a graphical representation its preferred nature, such as spatial or temporal relationships. Due to the nature of these applications, it is very important that key-details are made easy to identify. In the context of the VAST 2008 Challenge, we developed a visualization tool that graphically displays the movement of 82 employees of the Miami Department of Health (USA). We also asked 13 users to identify potential suspects and observe what happened during an evacuation of the building caused by an explosion. In this paper we explain the results of the user testing we conducted and how the users interpreted the event taken into account.
Evaluating the relationship between user interaction and financial visual analysis
Authors: Dong Hyun Jeong, Wenwen Dou, Heather Lipford, Felesia Stukes, Remco Chang, William Ribarsky
Published at VAST, 2008

It has been widely accepted that interactive visualization techniques enable users to more effectively form hypotheses and identify areas for more detailed investigation. There have been numerous empirical user studies testing the effectiveness of specific visual analytical tools. However, there has been limited effort in connecting a userpsilas interaction with his reasoning for the purpose of extracting the relationship between the two. In this paper, we present an approach for capturing and analyzing user interactions in a financial visual analytical tool and describe an exploratory user study that examines these interaction strategies. To achieve this goal, we created two visual tools to analyze raw interaction data captured during the user session. The results of this study demonstrate one possible strategy for understanding the relationship between interaction and reasoning both operationally and strategically.
Generating hypotheses of trends in high-dimensional data skeletons
Authors: Chandan K. Reddy, Snehal Pokharkar, Tin Kam Ho
Published at VAST, 2008

We seek an information-revealing representation for high-dimensional data distributions that may contain local trends in certain subspaces. Examples are data that have continuous support in simple shapes with identifiable branches. Such data can be represented by a graph that consists of segments of locally fit principal curves or surfaces summarizing each identifiable branch. We describe a new algorithm to find the optimal paths through such a principal graph. The paths are optimal in the sense that they represent the longest smooth trends through the data set, and jointly they cover the data set entirely with minimum overlap. The algorithm is suitable for hypothesizing trends in high-dimensional data, and can assist exploratory data analysis and visualization.
Grand challenge award 2008: Support for diverse analytic techniques - nSpace2 and GeoTime visual analytics
Authors: Lynn Chien, Annie Tat, Pascale Proulx, Adeel Khamisa, William Wright
Published at VAST, 2008

GeoTime and nSpace2 are interactive visual analytics tools that were used to examine and interpret all four of the 2008 VAST Challenge datasets. GeoTime excels in visualizing event patterns in time and space, or in time and any abstract landscape, while nSpace2 is a web-based analytical tool designed to support every step of the analytical process. nSpace2 is an integrating analytic environment. This paper highlights the VAST analytical experience with these tools that contributed to the success of these tools and this team for the third consecutive year.
Grand challenge award: Data integration visualization and collaboration in the VAST 2008 Challenge
Authors: Donald A. Pellegrino, Chi-Chun Pan, Anthony C. Robinson, Michael Stryker, Junyan Luo, Chris E. Weaver, Prasenjit Mitra, Chaomei Chen, Ian Turton, Alan M. MacEachren
Published at VAST, 2008

The VAST 2008 Challenge consisted of four heterogeneous synthetic data sets each organized into separate mini-challenges. The Grand Challenge required integrating the raw data from these four data sets as well as integrating results and findings from team members working on specific mini-challenges. Modeling the problem with a semantic network provided a means for integrating both the raw data and the subjective findings.
Grand challenge award: Interactive visual analytics palantir: The future of analysis
Authors: Jason Payne, Jake Solomon, Ravi Sankar, Bob McGrew
Published at VAST, 2008

Palantir is a world-class analytic platform used worldwide by governmental and financial analysts. This paper provides an introduction to the platform contextualized by its application to the 2008 IEEE VAST contest. In this challenge, we explored a notional dataset about a fabricated religious movement, Catalanopsilas Paraiso Manifesto Movement.
Interactive poster - SocialRank: An ego- and time-centric workflow for relationship identification
Authors: Jaime Montemayor, Christopher P. Diehl, Michael J. Pekala, David Patrone
Published at VAST, 2008

From instant messaging and email to wikis and blogs, millions of individuals are generating content that reflects their relationships with others in the world, both online and offline. Since communication artifacts are recordings of life events, we can gain insights into the social attributes and structures of the people within this communication history. In this paper, we describe SocialRank, an ego- and time-centric workflow for identifying social relationships in an email corpus. This workflow includes four high-level tasks: discovery, validation, annotation and dissemination. SocialRank combines relationship ranking algorithms with timeline, social network diagram, and multidimensional scaling visualization techniques to support these tasks.
Interactive poster: Visual analytic techniques for CO₂ emissions and concentrations in the United States
Authors: Nathan Andrysco, Bedrich Benes, Kevin R. Gurney
Published at VAST, 2008

Climate change has emerged as one of the grand global challenges facing humanity. The dominant anthropogenic greenhouse gas that seems to be contributing to the climate change problem, carbon dioxide (CO2), has a complex cycle through the atmosphere, oceans and biosphere. The combustion of fossil fuels (power production, transportation, etc.) remains the largest source of anthropogenic CO2 to the Earthpsilas atmosphere. Up until very recently, the quantification of fossil fuel CO2 was understood only at coarse space and time scales. A recent research effort has greatly improved this space/time quantification resulting in source data at a resolution of less than 10 km2/hr at the surface of North America. By providing visual tools to examine this new, high resolution CO2 data, we can better understand the way that CO2 is transmitted within the atmosphere and how it is exchanged with other components of the Earth System. We have developed interactive visual analytic tools, which allows for easy data manipulation, analysis, and extraction. The visualization system is aimed for a wide range of users which include researchers and political leaders. The goal is to help assist these people in analyzing data and enabling new policy options in mitigation of fossil fuel CO2 emissions in the U.S.