In consumer research, understanding consumer behavior and experiences is vital for making informed decisions about product design, innovation and marketing. Zaltman's Metaphor Elicitation Technique (ZMET) leverages metaphors and non-verbal communication to uncover and gain deeper insights into consumers' thoughts and emotions. This paper introduces a novel system that enables consumer researchers (interviewers) to perform a modified version of metaphor elicitation interviews in virtual reality (VR). Consumers (participants) use 3D objects in the virtual environment to express their thoughts and emotions, instead of pictures conventionally used in a ZMET interview. The system features an asymmetric setup where the participant is immersed in VR using a head-mounted display (HMD), while the interviewer views the participant's perspective on a monitor. We discuss the technical and design aspects of the VR system and present the results of a user study (N=17) that we conducted to validate the effectiveness of performing the metaphor elicitation interviews in VR. This work also explores the experiences of both participants and interviewers during the interview sessions, aiming to identify potential improvements. The qualitative and quantitative analysis of the data demonstrated how immersion, presence and embodied interaction positively affect and aid in sense-making and deeper expression of the participants' thoughts, perspectives and emotions.

Hummingbird is an innovative, award-winning performance engaging participants in active storytelling that bridges live theater and collaborative interaction through virtual reality (VR). Hummingbird's story celebrates courage and coming of age through the eyes of a gutsy teen who must outsmart her mother's egotistic boss and survive a dangerous new technology in a live, immersive adventure. Developed at the University of Illinois Chicago by faculty and over 30 students from the departments of Computer Science and Design in partnership with professional theater producers, directors, actors, videographers and composers, this project advanced interdisciplinary collaboration, provided a unique learning environment and broadened the research experience for several cohorts of students. Over 500 people attended Hummingbird's performances at the Tony Award-winning Goodman Theatre's New Stages Festival, Chicago Children's Theater and SIGGRAPH 2022 in Vancouver, Canada, with over 200 active VR participants. In each performance, five VR participants actively collaborate with each other and a lead actor within the VR adventure, contributing problem-solving, collaboration and teamwork, while a greater audience simultaneously follows the virtual performance aspects on a large video wall in real-time. Discussion sessions and audience evaluations followed each performance, informed the Hummingbird team on script, design and interactivity to improve future performances. Through qualitative analysis of audience experiences and insights from our collaboration, we discuss key considerations and design recommendations for integrating VR with live theater. Hummingbird demonstrates how VR can revolutionize theatrical storytelling by enabling traditional theater to narrate epic stories that were once considered too ambitious for traditional stage by extending live theater and making VR accessible to a broader audience. This project serves as a prototype for successful partnerships between nonprofit theater and interdisciplinary research institutions to increase opportunities for cross-disciplinary student education.

Natural Language Interfaces that facilitate data exploration tasks are rapidly gaining in interest in the research community because they enable users to focus their attention on the task of inquiry rather than the mechanics of chart construction. Yet, current systems rely solely on processing the user’s explicit commands to generate the user’s intended chart. These commands can be ambiguous due to natural language tendencies such as speech disfluency and underspecification. In this paper, we developed and studied how an always listening interface can help contextualize imprecise queries. Our study revealed that an always listening interface is able to use an on-going conversation to fill in missing properties for imprecise commands, disambiguate inaccurate commands without asking the user for clarification, as well as generate charts without being explicitly asked.

Abari Bhattacharya, Abhinav Kumar, Barbara Di Eugenio, Roderick Tabalba, Jillian Aurisano, Veronica Grosso, Andrew Johnson, Jason Leigh, Moira Zellner. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue. 2023.

Technology have long been a partner of workplace meeting facilitation. The recent outbreak of COVID-19 and the cautionary measures to reduce its spread have made it more prevalent than ever before in the form of online-meetings. In this paper, we recount our experiences during weekly meetings in three modalities: using SAGE2 - a collaborative sharing software designed for large displays - for co-located meetings, using a conventional projector for co-located meetings, and using the Zoom video-conferencing tool for distributed meetings. We view these meetings through the lens of effective meeting attributes and share ethnographic observations and attitudinal survey conducted in our research lab. We discuss patterns of content sharing, either sequential, parallel, or semi-parallel, and the potential advantages of creating complex canvases of content. We see how the SAGE2 tool affords parallel content sharing to create complex canvases, which represent queues of ideas and contributions (past, present, and future) using the space on a large display to suggest the progression of time through the meeting.

Our goal is to develop an intelligent assistant to support users explore data via visualizations. We have collected a new corpus of conversations, CHICAGO-CRIME-VIS, geared towards supporting data visualization exploration, and we have annotated it for a variety of features, including contextualized dialogue acts. In this paper, we describe our strategies and their evaluation for dialogue act classification. We highlight how thinking aloud affects interpretation of dialogue acts in our setting and how to best capture that information. A key component of our strategy is data augmentation as applied to the training data, since our corpus is inherently small. We ran experiments with the Balanced Bagging Classifier (BAGC), Condiontal Random Field (CRF), and several Long Short Term Memory (LSTM) networks, and found that all of them improved compared to the baseline (e.g., without the data augmentation pipeline). CRF outperformed the other classification algorithms, with the LSTM networks showing modest improvement, even after obtaining a performance boost from domain-trained word embeddings. This result is of note because training a CRF is far less resource-intensive than training deep learning models, hence given a similar if not better performance, traditional methods may still be preferable in order to lower resource consumption.

Abstract This paper describes results from an observational, exploratory study of visual data exploration in a large, multi‐view, flexible canvas environment. Participants were provided with a set of data exploration sub‐tasks associated with a local crime dataset and were instructed to pose questions to a remote mediator who would respond by generating and organizing visualizations on the large display. We observed that participants frequently posed requests to cast a net around one or several subsets of the data or a set of data attributes. They accomplished this directly and by utilizing existing views in unique ways, including by requesting to copy and pivot a group of views collectively and posing a set of parallel requests on target views expressed in one command. These observed actions depart from multi‐view flexible canvas environments that typically provide interfaces in support of generating one view at a time or actions that operate on one view at a time. We describe how participants used these ‘cast‐a‐net’ requests for tasks that spanned more than one view and describe design considerations for multi‐view environments that would support the observed multi‐view generation actions.

SAGE (the Scalable Adaptive Graphics Environment) and its successor SAGE2 (the Scalable Amplified Group Environment) are operating systems for managing content across wideband display environments. This paper documents the prevalent usage patterns of SAGE-enabled display walls in support of the e-Science enterprise, based on nearly 15 years of observations of the SAGE community. These patterns will help guide e-Science users and cyberinfrastructure developers on how best to leverage large tiled display walls, and the types of software services that could be provided in the future.

In today's Big Data era, data scientists require new computational instruments in order to quickly analyze large-scale datasets using complex codes and quicken the rate of scientific progress. While Federally-funded computer resources, from supercomputers to clouds, are beneficial, they are often limiting - particularly for deep learning and visualization - as they have few Graphics Processing Units (GPUs). GPUs are at the center of modern high-performance computing and artificial intelligence, efficiently performing mathematical operations that can be massively parallelized, speeding up codes used for deep learning, visualization and image processing, more so than general-purpose microprocessors, or Central Processing Units (CPUs). The University of Illinois at Chicago is acquiring a much-in-demand GPU-based instrument, COMPaaS DLV - COMposable Platform as a Service Instrument for Deep Learning & Visualization, based on composable infrastructure, an advanced architecture that disaggregates the underlying compute, storage, and network resources for scaling needs, but operates as a single cohesive infrastructure for management and workload purposes. We are experimenting with a small system and learning a great deal about composability, and we believe COMPaaS DLV users will benefit from the varied workflow that composable infrastructure allows.

Multi device environments present new opportunities for collaborative visual data analysis and sense making by utilizing each device's strengths and capabilities. However, one of the associated challenges with visual data analysis in multi device environments is the sharing of visual components across devices. We present a framework developed on top of SAGE2 platform for cross-device collaborative visual data exploration. As part of our framework, we contribute the concept of rapid development and assembling of visualizations that can span multiple devices of different modalities. It provides the users with an environment for visualization compositions that delegate the rendering to the target device, allowing them to augment their large display workspace with portable devices for further exploration territories. Facilitated by its intuitive visualization composition pipeline, users with no programming skills such as data analysts can enhance their analytical scope with no coding barriers. We describe the framework, its implementation with a use case, and the rationale behind its design.

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronized sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.

Abhinav Kumar, Jillian Aurisano, Barbara Di Eugenio, Andrew Johnson, Alberto Gonzalez, Jason Leigh. Proceedings of the 17th Annual Meeting of the Special Interest Group on Discourse and Dialogue. 2016.

Classic visual analysis relies on a single medium for displaying and interacting with data. Large-scale tiled display walls, virtual reality using head-mounted displays or CAVE systems, and collaborative touch screens have all been utilized for data exploration and analysis. We present our initial findings of combining numerous display environments and input modalities to create an interactive multi-modal display space that enables researchers to leverage various pieces of technology that will best suit specific sub-tasks. Our main contributions are 1) the deployment of an input server that interfaces with a wide array of interaction devices to create a single uniform stream of data usable by custom visual applications, and 2) three real-world use cases of leveraging multiple display environments in conjunction with one another to enhance scientific discovery and data dissemination.

Real world group-to-group collaboration often occurs between partially distributed interdisciplinary teams, with each discipline working in a unique environment suited for its needs. Groupware must be flexible so that it can be incorporated into a variety of workspaces in order to successfully facilitate this type of mixed presence collaboration. We have developed two new techniques for sharing and synchronizing multi-user applications between heterogeneous large-scale shared displays. The first new technique partitions displays into a perfectly mirrored public space and a local private space. The second new technique enables user-controlled partial synchronization, where different attributes of an application can be synchronized or controlled independently. This paper presents two main contributions of our work: 1) identifying deficiencies in current groupware for interacting with data during mixed presence collaboration, and 2) developing two multi-user data synchronization techniques to address these deficiencies and extend current collaborative infrastructure for large-scale shared displays.

Large high-resolution displays are becoming increasingly common in research settings, providing data scientists with visual interfaces for the analysis of large datasets. Numerous studies have demonstrated unique perceptual and cognitive benefits afforded by these displays in visual analytics and information visualization tasks. However, the effects of these displays on knowledge discovery in exploratory visual analysis are still poorly understood. We present the results of a small-scale study to better understand how display size and resolution affect insight. Analyzing participants' verbal statements, we find preliminary evidence that larger displays with more pixels can significantly increase the number of discoveries reported during visual exploration, while yielding broader, more integrative insights. Furthermore, we find important differences in how participants performed the same visual exploration task using displays of varying sizes. We tie these results to extant work and propose explanations by considering the cognitive and interaction costs associated with visual exploration.

Achievable networking performance of applications in a supercomputer depends on the exact combination of the communication patterns of the applications and the routing algorithms used by the supercomputer. In order to achieve the highest networking performance for the applications the routing algorithms need to be designed optimally for those communication patterns. However, while communication patterns usually have a wide variation from application to application and even from phase to phase in an application, routing algorithms have a limited variation and usually are optimized for typical communication patterns. This results in high networking performance for favored communication patterns but low networking performance for others. In this paper we present approaches for improving networking performance by rebalancing load on physical links on the Blue Gene Q supercomputer. We realize our approaches in a framework called OPTIQ and demonstrate the efficacy of our framework via a set of benchmarks. Our results show that we can achieve 30% higher throughput on experiment with data and patterns from a real application. The improvement can be up to several times higher throughput than default MPI_Alltoallv used in the Blue Gene Q supercomputer for certain communication patterns.

Achievable networking performance of applications in a supercomputer depends on the exact combination of the communication patterns of the applications and the routing algorithms used by the supercomputer. In order to achieve the highest networking performance for the applications, the routing algorithms need to be designed optimally for those communication patterns. However, while communication patterns usually vary from application to application and even from phase to phase in an application, routing algorithms have limited variation and usually are optimized for typical communication patterns. This results in high networking performance for some communication patterns. In this paper we present approaches for improving communication performance by using multiple paths and re-balancing load on physical links on the Blue Gene/Q supercomputer. We realize our approaches in a framework called OPTIQ and demonstrate the efficacy of our framework via a set of benchmarks. Our results show that we can achieve 43 -- 67% higher throughput on average from 91 experiments, and can achieve higher throughput than default MPI_Alltoallv used for certain communication patterns.

BACKGROUND: The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. RESULTS: In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. CONCLUSIONS: BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.

Current web-based collaboration systems, such as Google Hangouts, WebEx, and Skype, primarily enable single users to work with remote collaborators through video conferencing and desktop mirroring. The original SAGE software, developed in 2004 and adopted at over one hundred international sites, was

In the domain of large-scale visualization instruments, hybrid reality environments (HREs) are a recent innovation that combines the best-in-class capabilities of immersive environments, with the best-in-class capabilities of ultra-high-resolution display walls. HREs create a seamless 2D/3D environment that supports both information-rich analysis as well as virtual reality simulation exploration at a resolution matching human visual acuity. Co-located research groups in HREs tend to work on a variety of tasks during a research session (sometimes in parallel), and these tasks require 2D data views, 3D views, linking between them and the ability to bring in (or hide) data quickly as needed. In this paper we present Omegalib, a software framework that facilitates application development on HREs. Omegalib is designed to support dynamic reconfigurability of the display environment, so that areas of the display can be interactively allocated to 2D or 3D workspaces as needed. Compared to existing frameworks and toolkits, Omegalib makes it possible to have multiple immersive applications running on a cluster-controlled display system, have different input sources dynamically routed to applications, and have rendering results optionally redirected to a distributed compositing manager. Omegalib supports pluggable front-ends, to simplify the integration of third-party libraries like OpenGL, OpenSceneGraph, and the Visualization Toolkit (VTK). We present examples of applications developed with Omegalib for the 74-megapixel, 72-tile CAVE2™ system, and show how a Hybrid Reality Environment proved effective in supporting work for a co-located research group in the environmental sciences.

This video describes the CAVE2 Hybrid Reality Environment developed by the Electronic Visualization Laboratory (EVL) at the University of Illinois at Chicago (UIC). CAVE2 is a near-seamless flat-panel-based, surround-screen immersive system that can simultaneously display both 2D and 3D information, providing more flexibility for mixed media applications and more opportunities for groups of researchers to work together with large heterogeneous datasets [1]. CAVE2 is a cylindrical system of 24 feet in diameter and 8 feet tall, and consists of 72 near-seamless, off-axis-optimized passive-stereo LCD panels, creating a 320-degree panoramic environment for displaying information at 37 Megapixels (in stereoscopic 3D) or 74 Megapixels in 2D and at a horizontal visual acuity of 20/20 [2]. Custom LCD panels with shifted polarizers were built so the images in the top and bottom rows of LCDs are optimized for vertical off-center viewing, allowing viewers to come closer to the displays while minimizing ghosting. EVL's Omegalib middleware supports fully immersive OpenGL, OpenSceneGraph and VTK applications, as well as EVL's SAGE middleware to achieve a hybrid 2D/3D environment. CAVE2 also supports CalVR (developed at the Calit2 Qualcomm Institute at University of California, San Diego), Electro (by Robert Kooima, currently at Louisiana State University) and Google Earth.

This article will describe the progress since 2000 on research and development in 2-D and 3-D scalable resolution display walls that are built from tiling individual lower resolution flat panel displays. The article will describe approaches and trends in display hardware construction, middleware architecture, and user-interaction design. The article will also highlight examples of use cases and the benefits the technology has brought to their respective disciplines.

Abstract Social network analysis is the study of patterns of interaction between social entities. The field is attracting increasing attention from diverse disciplines including sociology, epidemiology, and behavioral ecology. An important sociological phenomenon that draws the attention of analysts is the emergence of communities, which tend to form, evolve, and dissolve gradually over a period of time. Understanding this evolution is crucial to sociologists and domain scientists, and often leads to a better appreciation of the social system under study. Therefore, it is imperative that social network visualization tools support this task. While graph‐based representations are well suited for investigating structural properties of networks at a single point in time, they appear to be significantly less useful when used to analyze gradual structural changes over a period of time. In this paper, we present an interactive visualization methodology for dynamic social networks. Our technique focuses on revealing the community structure implied by the evolving interaction patterns between individuals. We apply our visualization to analyze the community structure in the US House of Representatives. We also report on a user study conducted with the participation of behavioral ecologists working with social network datasets that depict interactions between wild animals. Findings from the user study confirm that the visualization was helpful in providing answers to sociological questions as well as eliciting new observations on the social organization of the population under study.

Many interrelated planetary height map and surface image map data sets exist, and more data are collected each day. Broad communities of scientists require tools to compose these data interactively and explore them via real-time visualization. While related, these data sets are often unregistered with one another, having different projection, resolution, format, and type. We present a GPU-centric approach to the real-time composition and display of unregistered-but-related planetary-scale data. This approach employs a GPGPU process to tessellate spherical height fields. It uses a render-to-vertex-buffer technique to operate upon polygonal surface meshes in image space, allowing geometry processes to be expressed in terms of image processing. With height and surface map data processing unified in this fashion, a number of powerful composition operations may be uniformly applied to both. Examples include adaptation to nonuniform sampling due to projection, seamless blending of data of disparate resolution or transformation regardless of boundary, and the smooth interpolation of levels of detail in both geometry and imagery. Issues of scalability and precision are addressed, giving out-of-core access to giga-pixel data sources, and correct rendering at scales approaching one meter.

A solid-state dynamic parallax barrier autostereoscopic display mitigates some of the restrictions present in static barrier systems, such as fixed view-distance range, slow response to head movements, and fixed stereo operating mode. By dynamically varying barrier parameters in real time, viewers may move closer to the display and move faster laterally than with a static barrier system, and the display can switch between 3D and 2D modes by disabling the barrier on a per-pixel basis. Moreover, Dynallax can output four independent eye channels when two viewers are present, and both head-tracked viewers receive an independent pair of left-eye and right-eye perspective views based on their position in 3D space. The display device is constructed by using a dual-stacked LCD monitor where a dynamic barrier is rendered on the front display and a modulated virtual environment composed of two or four channels is rendered on the rear display. Dynallax was recently demonstrated in a small-scale head-tracked prototype system. This paper summarizes the concepts presented earlier, extends the discussion of various topics, and presents recent improvements to the system.

A novel barrier strip autostereoscopic (AS) display is demonstrated using a solid-state dynamic parallax barrier. A dynamic barrier mitigates restrictions inherent in static barrier systems such as fixed view distance range, slow response to head movements, and fixed stereo operating mode. By dynamically varying barrier parameters in real time, viewers may move closer to the display and move faster laterally than with a static barrier system. Furthermore, users can switch between 3D and 2D modes by disabling the barrier. Dynallax is head-tracked, directing view channels to positions in space reported by a tracking system in real time. Such head-tracked parallax barrier systems have traditionally supported only a single viewer, but by varying the barrier period to eliminate conflicts between viewers, Dynallax presents four independent eye channels when two viewers are present. Each viewer receives an independent pair of left and right eye perspective views based on their position in 3D space. The display device is constructed using a dual-stacked LCD monitor where a dynamic barrier is rendered on the front display and the rear display produces a modulated VR scene composed of two or four channels. A small-scale head-tracked prototype VR system is demonstrated.

LambdaGrid applications as typified by data-intensive collaborative visualization are likely to be the first users of terabit-level networking. This paper features a main enabler of collaborative visualization over LambdaGrid, the Scalable Adaptive Graphics Environment (SAGE) in particular, and anticipates the future needs of LambdaGrid applications in general. We present a scalable architecture called LambdaBridge to 'bridge' LambdaGrid applications with the terabit optical core networks. LambdaBridge will provision and control predictable- performance networks for end-systems (i.e. Grid clusters) using on-demand lambda/VLAN provisioning and end-system traffic shaping. The chief contribution of LambdaBridge is a deep understanding of how to synergistically bridge provisionable networks, end-systems, and future generation distributed terabit applications. This paper also introduces Scalable Visualcasting - a multicasting service for LambdaGrid that incorporates IP multicasting and optical multicasting.

The Scalable Adaptive Graphics Environment (SAGE) is specialized middleware for enabling data, high-definition video and extremely high-resolution graphics to be streamed in real-time from remotely distributed rendering and storage clusters to scalable display walls over ultra-high-speed networks. In this paper, we present the SAGE architecture, focusing on its dynamic graphics streaming capability. In the SAGE framework, multiple visualization applications can be streamed to large tiled displays and viewed at the same time. The application windows can be moved, resized and overlapped like any standard desktop window manager. Every window movement or resize operation requires dynamic and non-trivial reconfiguration of the involved graphics streams. This approach has been successfully shown to scale to support streaming on the LambdaVision 100 Megapixel display wall. SAGE is now being extended to support distance collaboration with multiple endpoints by streaming visualization to all the participants.

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive prefetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization.

In electronically mediated distance collaborations involving scientific data, there is often the need to stream the graphical output of individual computers or entire visualization clusters to remote displays. This work presents TeraVision as a scalable platform-independent solution which is capable of transmitting multiple synchronized high-resolution video streams between single workstations and/or clusters without requiring any modifications to be made to the source or destination machines. Issues addressed include: how to synchronize individual video streams to form a single larger stream; how to scale and route streams generated by an array of M/spl times/N nodes to fit a X/spl times/Y display; and how TeraVision exploits a variety of transport protocols. Results from experiments conducted over gigabit local-area networks and wide-area networks (between Chicago and Amsterdam), are presented. Finally, we propose the scalable adaptive graphics environment (SAGE) - an architecture to support future collaborative visualization environments with potentially billions of pixels.

We present the current state of Vol-a-Tile, an interactive tool for exploring large volumetric data on scalable tiled displays. Vol-a-Tile presents a variety of features employed by scientists at the Scripps Institution of Oceanography on data collected from the Anatomy of a Ridge-Axis Discontinuity seismic experiment. Hardware texture mapping and level-of-detail techniques provide interactivity. A high-performance network protocol is used to connect remote data sources over high-bandwidth photonic networks.

Kevin Harris' sixth grade class has a mission; they need to find out why there are more red flowers in certain areas of a large field. Mr. Harris breaks up the class into groups to explore different parts of the field. When the children come upon a flower, they place a flag in the ground to mark the spot and record its position and colour using a pocket PC that doubles as a Global Positioning System (GPS) receiver. They do all of this at an ImmersaDesk/sup TM/ in their school. Once all of the data is collected, the students meet as a group in their classroom to integrate and visualize it. Patterns that are not visible while collecting the data suddenly appear when that data is visualized as a whole. Using MyWorld, a geographic information system for high-school students, filters are applied to the data to make the patterns more obvious. This collaboration combines the VR educational work at the University of Illinois at Chicago with the desktop educational work at Northwestern University. It is part of a larger NSF funded project including the University of Michigan and Georgia Tech developing guidelines and an engineering process to support software developers in building effective computer-based learning environments.

This paper presents our findings after the first year and a half of a multi-year deployment of an ImmersaDesk/sup (R)/ to a local elementary school, investigating its effectiveness in enhancing science education. These findings deal with how VR can aid in the coordination of multiple representations, and how to integrate the technology into the existing school culture.

This paper describes the design and implementation of CAVERNsoft G2, a toolkit for building collaborative virtual reality applications. G2's special emphasis is on providing the tools to support high-performance computing and data intensive systems that are coupled to collaborative, immersive environments.This paper describes G2's broad range of services, and demonstrates how they are currently being used in a collaborative volume visualization application.

A distributed immersive virtual environment was deployed as a component of a pedagogical strategy for teaching third grade children that the Earth is round. The displacement strategy is based on the theory that fundamental conceptual change requires an alternative cognitive starting point which doesnt invoke the features of pre-existing models. While the VR apparatus helped to establish that alternative framework, conceptual change was strongly influenced by the bridging activities which related that experience to the target domain. Simple declarations of relevance proved ineffective. A more articulated bridging process involving physical models was effective for some children, but the multiple representations employed required too much model-matching for others.

This paper proposes a methodology for employing collaborative, immersive virtual environments as a high-end visualization interface for massive data-sets. The methodology employs feature detection, partitioning, summarization and decimation to significantly cull massive data-sets. These reduced data-sets are then distributed to the remote CAVEs, ImmersaDesks and desktop workstations for viewing. The paper also discusses novel techniques for collaborative visualization and meta-data creation.

The paper discusses a virtual mail system. V-mail is designed to be used in the CAVE virtual environment. The participants' mail messages and the ongoing modifications of the VE are maintained by a central server. V-mail's user interface is embodied in a virtual friend or pet that follows the participant as he/she interacts with the VE.

The Round Earth Project is investigating how virtual reality technology can be used to help teach concepts that are counter-intuitive to a learner's currently held mental model. Virtual reality can be used to provide an alternative cognitive starting point that does not carry the baggage of past experiences. In particular this paper describes our work in comparing two strategies for teaching young children that the Earth is spherical when their everyday experiences tell them it is flat.

This paper presents an overview of the tele-immersion applications that have been built by collaborators around the world using the CAVERNsoft toolkit, and the lessons learned from building these applications. In particular the lessons learned are presented as a set of rules-of-thumb for developing tele-immersive applications in general.

The development of applications and tools for high-performance "computational grids" is complicated by the heterogeneity and frequently dynamic behavior of the underlying resources; by the complexity of the applications themselves, which often combine aspects of supercomputing and distributed computing; and by the need to achieve high levels of performance. The Globus toolkit has been developed with the goal of simplifying this application development task, by providing implementations of various core services deemed essential for high-performance distributed computing. In this paper, we describe two large applications developed with this toolkit: a distributed interactive simulation and a teleimmersion system. We describe the process used to develop the applications, review the lessons learned and draw conclusions regarding the effectiveness of the toolkit approach.

The Electronic Visualization Laboratory (EVL) at the University of Illinois at Chicago (UIC) has partnered with dozens of computational scientists and engineers to create visualization and virtual reality (VR) devices and applications for collaborative exploration of scientific and engineering data. Since 1995, our research and development activities have incorporated emerging high bandwidth networks like the vBNS and the Internet2 in an effort now called Tele-Immersion. As a result of our six years' experience in building first and second generation VR devices to support these applications, we consider third generation VR devices that will provide desktop/office sized displays. Since no current technology is yet configurable with ideal resolution and size, we will first simulate these devices with available parts, and then build more advanced prototypes. We believe that the devices we propose to build using the new display technologies form a set of desirable human/computer interface requirements for successful Tele-Immersion adoption. A goal of this research is to develop clearly compelling prototypes so that these devices can be improved and reproduced by the private sector.

Much of the data that is stored in scientific databases is collected through experimentation. We propose a new interface to scientific databases: the SANDBOX: Scientists Accessing Necessary Data Based On eXperimentation. The SANDBOX is a virtual reality tool which allows an investigator to recreate the original experiment. The investigator places virtual instruments into a virtual reenactment of the original experiment and collects data from the scientific database in much the same way that the original data was collected. These instruments give visual and auditory feedback, allowing the user to browse through data of any type. We have implemented a prototype of the SANDBOX on NASA's FIFE scientific database using the CAVE virtual reality theatre.>