The visualization of space-time trajectory data is challenging due to the fact that, in most cases, the data inherently exists in more than two dimensions. In many space-time visualizations, additional variables must be mapped into other visual attributes such as color or size. Given that substantive analyses of trajectory data will likely be concerned with variables beyond space and time, we propose a method that allows trajectory positions to be determined by an arbitrary number of variables in a multi-dimensional space-time dataset. Our method is based on Star Coordinates, a prior technique for interactively positioning multi-dimensional data. Our technique is catered specifically to multi-dimensional space-time trajectory data. The technique is demonstrated using a large multi-dimensional space-time dataset related to touring musicians.

StretchPlot showing 30-day moving average trajectories

StretchPlot: Interactive Visualization of Multi-Dimensional Trajectory Data

Visualization practitioners have traditionally focused on evaluating the outcome of the visual analytic process, as opposed to studying how that process unfolds. Since user strategy would likely influence the outcome of visual analysis and the nature of insights acquired, it is important to understand how the analytic behavior of users is shaped by variations in the design of the visualization interface. This paper presents a technique for evaluating user behavior in exploratory visual analysis scenarios. We characterize visual exploration as a fluid activity involving transitions between mental and interaction states. We show how micro-patterns in these transitions can be captured and analyzed quantitatively to reveal differences in the exploratory behavior of users, given variations in the visualization interface. 
Categories and Subject Descriptors 
H.5.2 [Information Interfaces and Presentation]: User Interfaces/Evaluation/methodology 
Keywords 
Exploratory visual analysis; insight-based evaluation.

Large display environment showing distribution of visualization content.

Evaluating User Behavior and Strategy During Visual Exploration

This paper describes the creation of SwarmVision, a system of autonomous robotic cameras that functions both as the basis for an art installation and as an instrument for generating novel engineering research. Through a series of interviews with engineers who examined the project, we illustrate how experimentation with the instrument could lead to potential new research directions in computer vision, machine learning, swarm robotics, remote collaboration, and visualization. This suggests that an unstructured and aesthetic approach to research can inform and inspire new engineering research directions, within and beyond the scope of this particular project. 
Keywords: Media arts methodologies, computational photography, swarm robotics, autonomous robotic cameras, arts and engineering.

Camera view of autonomous image capture process viewed in the 3D virtual scene overview.

Generation of Engineering Research Directions through Artistic Process

Community structure analysis reveals the properties of social networks. The application of this analysis to evolving communities in dynamic networks can help understand how social interactions between individuals dynamically change and how the brain networks grow. Visualizing these communities becomes challenging since the time dimension is an important component in dynamic networks. The problem is still more complex as the biological neural networks have physical structures, and communities are used to explore functional groupings. Our interactive visualization technique is used for exploring the community structure of dynamic mouse brain correlation networks and behaviors of individual nodes in the networks through time. 
Keywords: Neural networks, dynamic communities, information visualization. 
Index Terms: H.5.2 [Information Interfaces & Presentation]: User Interfaces – Graphical User Interfaces (GUI).

Visualization of Dynamic Mouse Brain Network Communities

Visualizing Communities in Dynamic Mouse Brain Networks

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. Processing and analyzing the raw sonar data generated by automated surveys is challenging due to the presence of complex error sources like water chemistry, zero-depth variations, inertial navigation errors and multipath reflections. Furthermore, the complexity of the collected data makes it difficult to perform effective analysis on a standard display. Point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. 

In this paper we present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, large scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.

Environmental scientists analyzing sonar data from West Lake Bonney, Antarctica using the visualization tool inside the CAVE2&trade;

Parallel Processing and Immersive Visualization of Sonar Point Clouds

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. 

In other settings, it is possible to use optical methods to analyze the geometry of obstacles and features surrounding an autonomous vehicle, but the optical properties of underwater environments make this impossible. Sonar is still the best technology for underwater location, navigation and scanning. 

Sonar point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. 

We present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, larges scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.

The Environmentally Non Disturbing Underwater Robotic ANTarctic Explorer (ENDURANCE) AUV

Parallel Processing and Immersive Visualization of Sonar Data (poster)

Clinical Decision Support (CDS) systems have the potential of significantly improving the quality and efficiency of patient care, but they need to present information in a way that is easily understandable by health care personnel. In the clinical setting, nurses are often tasked with the care of a large number of patients, and in specific scenarios are in charge of independently making care decisions to improve patient comfort and for symptom relief care. We developed a CDS prototype embedded in a nursing hand-off management tool, which provides suggestions to adjust a plan of care based on a patient&rsquo;s profile. We show how presenting patient data and evidence in different forms (textual, tabular, graphical) has an impact on the efficiency of nurse decision making, and how a nurse&rsquo;s graphical literacy influences this process. 

Index Terms: Electronic Health Records, Clinical Decision Support, User Studies, User-centered Design

The target action rate trends for each user group versus graph literacy scores

One Size Doesn&rsquo;t Fit All: The Efficiency of Graphical, Numerical and Textual Clinical Decision Support for Nurses

Hearts and Minds: The Interrogations Project is an interactive Virtual Reality narrative performance made for the EVL&rsquo;s CAVE2&trade; large-scale 320-degree panoramic virtual reality environment that visualizes stories of violence and the post-traumatic stress experienced by ordinary American soldiers who became torturers in the course of serving their country. During the American-led counterinsurgency and counter-terrorism campaigns in Iraq in the years after September 11, 2001, the torture and abuse of detainees was a commonplace tactic. 

Keywords: Virtual reality, immersive environments, visualization, art, storytelling, digital humanities.

Hearts and Minds performance in the CAVE2&trade; panoramic virtual theater

Hearts and Minds: The Interrogations Project

Scagnostics (Scatterplot Diagnostics) were developed by Wilkinson et al., based on an idea of Paul and John Tukey, in order to discern meaningful patterns in large collections of scatterplots. The Tukeys&rsquo; original idea was intended to overcome the impediments involved in examining large scatterplot matrices (multiplicity of plots and lack of detail). Wilkinson&rsquo;s implementation enabled for the first time scagnostics computations on many points as well as many plots. Unfortunately, scagnostics are sensitive to scale transformations. We illustrate the extent of this sensitivity and show how it is possible to pair statistical transformations with scagnostics to enable discovery of hidden structures in data that are not discernible in untransformed visualizations. 

Keywords: Scagnostics, Scatterplot matrix, Transformation, High-Dimensional Visual Analytics

Inspecting the Outlying measure on the Sleep data: The selected variables are body weight vs. brain weight

Transforming Scagnostics to Reveal Hidden Features

Five public artworks are presented that feature data visualization situated in site-specific installations, each with distinct conditions of data collection, data analysis, audience interaction, and data archiving. This paper describes unique features of these projects and notes solutions to issues related especially to the staging of visual representation. Based on an examination of these issues, observed in different settings throughout the last decade, the paper concludes with an overview of key considerations specific to presenting data visualization in site-specific locations.

A data visualization showing checkout patterns from the Seattle Public Library over six years

Staging data visualization installations in site-specific situations

In this paper, we develop and implement approaches to user-driven predictive visual analytics on multivariate, spatio-temporal incident reporting data on the Lords Resistance Army (LRA) activity in Central Africa. We concentrate on specific predictive questions that pivot on LRA movement and cause-and-effect patterns. Our approach represents the output of simple models, such as a movement model and a local-related-incidents model. In addition, we provide users with interactive features to explore, which allows for the isolation of appropriate subsets of the data and visually separates signal from noise when addressing predictive questions. We implement this approach and use it to develop predictive hypotheses around variations in movement patterns of the LRA and to identify potential cause-and-effect patterns around the activity of commanders and solider defections. 
Index Terms: Visual analytics, prediction, spatio-temporal data

User-Driven Predictive Visual Analytics on Multivariate, Spatio-Temporal Incident Reports

This paper investigates the interactive projection of multivariate space-time data. Specifically, it investigates how complex datasets containing elements situated in space and time that include additional variables can be interactively explored to support effective multivariate geotemporal analyses. Given that substantive analyses of space-time trajectory data will likely be concerned with additional variables beyond space and time, we propose a novel technique, stretch projections, that allows trajectory positions to be determined by an arbitrary number of variables in a multidimensional space-time dataset. We present StretchPlot, an interactive prototype that allows multidimensional space-time trajectory data to be projected into a two-dimensional space according to multiple user-defined coordinate vectors. The StretchPlot tool is demonstrated using a large multidimensional space-time dataset that combines the trajectories of touring musicians with demographic data related to the locations of their performances. Examples are shown which identify relationships between multiple dimensions of space, time, and additional demographic variables, indicating that the use of of stretch projections may be useful for the exploratory analysis of multidimensional geotemporal data. 
Keywords:Space-time data, Trajectories, Culture, Sociological data, Stretch projections

Five views of Stretch Plot, revealing multivariate trends amongst a number of trajectories.

Interactively Exploring Geotemporal Relationships in Demographic Data via Stretch Projections

Interactive cellular automata systems for creative projects

Analysis / synthesis approaches for creatively processing video signals

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 designed to enable groups to work in front of large shared displays in order to solve problems that required juxtaposing large volumes of information in ultra high resolution. We have developed SAGE2, as a complete redesign and implementation of SAGE, using cloud-based and web browser technologies in order to enhance data intensive co-located and remote collaboration. This paper provides an overview of SAGE2&rsquo;s infrastructure, the technical design challenges, and the afforded benefits to data intensive collaboration. Lastly, we provide insight on how future collaborative applications can be developed to support large displays and demonstrate the power and flexibility that SAGE2 offers in collaborative scenarios through a series of use cases. 

Keywords: Large Displays; Co-located Collaboration; Remote Collaboration; Window Manager; Cloud Technologies; Multi-user Interaction; Computer Supported Cooperative Work

A typical SAGE2 session, depicting multiple applications windowed on a Scalable Resolution Shared Displays

SAGE2: A New Approach for Data Intensive Collaboration Using Scalable Resolution Shared Displays

The CAVE2 is a large-scale, 320-degree, 3D / 2D, virtual-reality environment developed by the Electronic Visualization Laboratory at the University of Illinois at Chicago. The environment has a tracking system that determines the location of the primary user, and then renders 3D images to his perspective. The CAVE2 also has a 20.2 channel sound system controlled by a SuperCollider-based audio server that is, in turn, controlled via the Omicron SoundAPI. Audio imaging for the system had operated with the assumption that the listener was stationary in the center of the CAVE2 and the individual source width of audio objects was not dynamically altered. Our team added functionality to maintain audio imaging, including source position and width, as a tracked user and sound object move relative to one another within the environment.

CAVE2 as located at the University of Chicago at Illinois&rsquo; Electronic Visualization Laboratory

Dynamic Audio Imaging in Radial Virtual Reality Environments

Evaluating density-based motion for Big Data visual analytics

Translation as technique: Collaboratively creating an electro-acoustic composition for saxophone and live video projection

Audio Dilation is a technique that slows down the tempo of audio signals without changing the pitch or otherwise distorting the sounds. Networked On-line Audio Dilation is an Android application that allows users to dilate audio while engaged in a full-duplex networked conversation. The capability can potentially be used to improve comprehension for hearing or cognitively impaired individuals, or for non-native speakers of foreign languages. 

Keywords: Speech modification; Audio dilation; Human augmentics

Networked On-line Audio Dilation Poster

Networked On-Line Audio Dilation

In-situ analysis has been proposed as a promising solution to glean faster insight and to reduce the amount of data written out to storage. A critical challenge here is that the reduced dataset needed to visualize a specific region of interest as the simulation is running is typically held on a subset of the nodes and needs to be written out to storage. Coupled multi-physics simulations also produce a sparse data pattern wherein data movement occurs among a subset of nodes. We evaluate the performance of these data patterns and propose several mechanisms for improving performance. Our mechanisms introduce intermediate nodes to implement multiple paths to transfer data on top of default routing algorithms and utilize topology-aware data aggregation to avoid shared bottleneck links. The efficacy of our solutions is evaluated through micro-benchmarks and application benchmarks on an IBM Blue Gene/Q system scaling up to 131,072 compute cores. The results show that our algorithms achieve up to a 2X improvement in achievable throughput compared to the default mechanisms. 

Keywords: multiple paths, sparse data movement, topology-aware aggregation, data-intensive, BG/Q

The ALCF maintains the 768K core Blue Gene/Q supercomputer (Mira), data analysis cluster (Tukey), and file server nodes

Improving Data Movement Performance for Sparse Data Patterns on the Blue Gene/Q Supercomputer

In this thesis, I present a novel genome data visualization targeting an important area of genomics research: comparative bacterial gene neighborhood analysis. This approach demands scalable visualization designs that accommodate simultaneous comparison of hundreds of genomes at once. 
Decreases in genome sequencing costs have driven a proliferation in the volume of genomic data. Thousands of complete genome sequences have been compiled on public databases and even larger volumes of data have been generated privately by independent research groups. In particular, rates of bacterial genome sequencing have accelerated, due to low sequencing costs. The comparative analysis of these genomes provides a new approach to the study of novel proteins and protein interactions. While automated analysis plays a significant role in the generation and analysis of this data, visualization is needed to bring experts into the data-mining loop, to verify the results of automated analysis and to detect patterns that are difficult to find through computation alone. 
At the same time, advances in display hardware have enabled similarly rapid growth in display resolution and the development of large, high-resolution environments. These environments present an opportunity to visualize big data in new ways and better integrate expert judgment in the computational analysis of big data. Recent research suggests that big displays present benefits to visualization designers and enable the analysis of complex data sets. However, more research is needed to understand the design decisions, such as perceptually scalable design, that best take advantage of these benefits. 
Genomic data visualizations have largely failed to keep pace with this growth in genomic data generation and display resolution. Existing visualizations are not designed to enable the comparison of more than a few genomes at once, and are built to work on moderate to low resolution environments. While it might seem reasonable to simply &rsquo;scale-up&rsquo; these visualizations to fill available screen space, in many cases the design of these approaches do not work on big displays. 
In this thesis, I present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a new comparative gene neighborhood visualization designed to address large volumes of bacterial genome sequences and explore the design decisions that best take advantage of large, high-resolution environments. I will describe the design of this approach and will characterize the ways in which this design scales to large numbers of comparisons, is suited to high-resolution environments, and adopts perceptually scalable encodings. My high-density genome data visualization approach relies on interactive visual queries to transform large data volumes into high-resolution comparative genomic maps, that use pre-attentive visual cues to address analytic tasks for comparative gene neighborhood investigations across large volumes of complete bacterial genomes. In addition, I present a visual algorithm that transforms the data into a view which simultaneously provides detail-up-close and context-from-a distance, allowing researchers to simultaneously access data at these two scales. 
The implementation of this approach is an interactive application that can run on single machine, tiled-display walls as well as high-resolution personal displays. I will describe the program design and architecture, along with several examples from visualizing draft Escherichia coli (E. coli) genomes. 
Preliminary results of this work suggest the novelty and significance of this approach, as well as potential areas of extension for this work. This approach adopts encodings that scale more effectively to large displays and large data volumes, enabling the rapid performance of analytic tasks across large data volumes. This approach also enables the simultaneous comparison and analysis of hundreds to thousands of genomic sequences, which greatly exceed the volumes possible in any existing tool. 
Future work in this area includes generalizing the approach to other sub-fields in comparative genomics. In addition, I will adapt this approach to be fit within an ecosystem of multiple-coordinated visualizations for tiled-display walls. I will also explore parallelization by adapting the rendering for the graphics processing unit, to achieve better interactivity. 
The primary contributions of this thesis are as follows: 
1) BactoGeNIE is a novel visualization design that is the first scalable visualization for comparative analysis of hundreds to thousands of gene neighborhoods. The state of the art competitor visualizations handle no more than 9 gene neighborhoods. 
2) BactoGeNIE is the first interactive &rsquo;thousand-genome&rsquo; comparative visual approach on the gene neighborhood scale combining navigation, details-on-demand, contig sorting, contig density control, ‘zoom’ and application of color tags to genes of interest. 
3) BactoGeNIE is the first to employ a dynamic &rsquo;gene targeting&rsquo; interaction which combines on-the-fly alignment and sorting by user selected ortholog clusters with the application of a color ramp for the target gene and contig, allowing for rapid hypothesis testing and the pre-attentive identification of commonly recurring neighbors, deletions, insertions, inversions, truncations, and potential errors in data processing. 
4) BactoGeNIE is the first to unify overviews with gene neighborhood details that can be accessed through physical movement. 
5) BactoGeNIE is the first gene neighborhood comparative visualization to be implemented for large, high-resolution environments.

BactoGeNIE running on a large, high-resolution environment after running the gene-targeting algorithm.

Bacterial Gene Neighborhood Investigation Environment: A Scalable Genome Visualization for Big Displays

As society continues to generate escalating quantities of data, there is an increasing demand for perceptual and cognitive aids to help us make sense of the available troves of digital information. Visualization represents one of the most effective ways for exploring large datasets by leveraging our visual-perceptual capacities. Unfortunately, the scalability of visualizations has been limited by the prevailing display technology. Conventional desktop and laptop displays provide too few pixels to visualize today&rsquo;s datasets, forcing users to contextually switch between different views in order to see alternate projections of the information space. This limitation has been known to reduce user performance and potentially hinder exploration by inducing a &lsquo;tunnel vision&rsquo; phenomenon where the analysis is focused on and limited to isolated subsets of the information space. However, thanks to advances in display technology, it is becoming increasingly feasible and affordable to surpass the limitations of conventional displays by building and acquiring Large High-resolution Displays. These displays are rapidly proliferating, providing researchers and scientists with more scalable platforms for the visual analysis and exploration of large and complex datasets. 

This dissertation investigates the impact of adopting large high-resolution displays on user strategy and insight acquisition during exploratory visual analysis. First, we present a theoretical account of the cognitive costs involved in visual exploration, and highlight the implicit role of the visualization interface in modulating these costs. Second, we propose design patterns for constructing coordinated, multi-view-based visualizations for large high-resolution displays. We then empirically investigate the effects of increasing the physical size and resolution of the visualization interface through observational and experimental studies. Our findings indicate improvement in discovery and insight acquisition, when users are provided with physically larger displays and more pixels. This effect manifests in a significant increase in the number of observations reported during visual exploration as well as the acquisition of higher-level, more integrative insights. These results suggest a role for large high-resolution displays in fostering discovery in data-intensive visual exploration scenarios.

User study in EVL&rsquo;s CAVE2&trade; showing correlations between various visualizations

Exploratory Visual Analysis in Large High-Resolution Display Environments

The e-cigarette survey prompt application is designed for Android smartphones. This mobile application allows researchers at the University of Illinois at Chicago to gain self-regulated data from all users involved in the study. This report details a previous project application, from which the application was design. A detailed explanation of the capabilities and user interactions with the application is documented through figures and text. Finally, the changes and complications which arose during the application&rsquo;s development are discussed, with the final product outlined at the end of the report. 

The effects of tobacco use have been long studied and are well understood. The carcinogens from smoking tobacco have been associated with a wide swath of terminal or debilitating ailments. Because of the serious health risks associated with smoking tobacco, cigarette use is well-regulated with long-standing legislation in place to help reduce its impact on individuals and the public. 

Recently, E-cigarettes have been developed and advertized as an acceptable, healthier alternative to smoking traditional tobacco cigarettes. However, there is no regulation in place for the use of e-cigarettes. E-cigarettes and electronic vaporizers are fairly new to the market and as of yet there are no warning labels on electronic tobacco paraphernalia, nor is there a ban on the sale of E-cigarettes to minors. In order for the Food and Drug Administration to regulate the manufacturing, marketing, and consumption of e-cigarette products, data must first be gathered on the characteristics of its users. 

Some of the main users of electronic tobacco products are young adults and people who want to quit smoking. A pervasive public opinion of e-cigarette users is that the vapor which they produce is not as harmful as the carcinogenic tobacco smoke of regular cigarettes. Unfortunately, not enough research reports have been published to substantiate this belief. The aim of this project was to better understand the usage patterns of young e-cigarette users and supply the federal Food and Drug Administration with these data.

Screenshot composition of login pages within the running e-cigarette survey application

E-cigarette Survey Prompt Application for Android Mobile Devices

Background: Knowledge of the 3D structure and functionality of proteins can lead to insight into the associated cellular processes, speed up the creation of pharmaceutical products, and develop drugs that are more effective in combating disease. 
Methods: We present the design and implementation of a visual mining and analysis tool to help identify protein mutations across a family of structural models and to help discover the effect of these mutations on protein function. We integrate 3D structure and sequence information in a common visual interface; multiple linked views and a computational backbone allow comparison at the molecular and atomic levels, while a novel trend-image visual abstraction allows for the sorting and mining of large collections of sequences and of their residues. 
Results: We evaluate our approach on the triosephosphate isomerase (TIM) family structural models and sequence data and show that our tool provides an effective, scalable way to navigate a family of proteins, as well as a means to inspect the structure and sequence of individual proteins. 
Conclusions: The TIM application shows that our tool can assist in the navigation of families of proteins, as well as in the exploration of individual protein structures. In conjunction with domain expert knowledge, this interactive tool can help provide biophysical insight into why specific mutations affect function and potentially suggest additional modifications to the protein that could be used to rescue functionality.

FixingTIM visual interface.

FixingTIM: Interactive Exploration of Sequence and Structural Data to Identify Functional Mutations in Protein Families

We introduce a web-based computing infrastructure to assist the visual integration, mining and interactive navigation of large-scale astronomy observations. Following an analysis of the application domain, we design a client-server architecture to fetch distributed image data and to partition local data into a spatial index structure that allows prefix-matching of spatial objects. In conjunction with hardware-accelerated pixel-based overlays and an online cross-registration pipeline, this approach allows the fetching, displaying, panning and zooming of gigabit panoramas of the sky in real time. To further facilitate the integration and mining of spatial and non-spatial data, we introduce interactive trend images - compact visual representations for identifying outlier objects and for studying trends within large collections of spatial objects of a given class. In a demonstration, images from three sky surveys
(SDSS, FIRST and simulated LSST results) are cross-registered and integrated as overlays, allowing cross-spectrum analysis of astronomy observations. Trend images are interactively generated from catalog data and used to visually mine astronomy observations of similar type. The front-end of the infrastructure uses the web technologies WebGL and HTML5 to enable cross-platform, web-based functionality. Our approach attains interactive rendering frame rates; its power and flexibility enables it to serve the needs of the astronomy community. Evaluation on three case studies, as well as feedback from domain experts emphasize the benefits of this visual approach to the observational astronomy field; and its potential benefits to large scale geospatial visualization in general. 
Index Terms: Data fusion and integration, scalability issues, geographic/geospatial visualization

Cross-correlated large-scale overlays of optical observations, radio-emission observations, and simulation results from the SDSS sky survey.

Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe

Users of social networks can be passionate about sharing their political convictions, art projects, or business ventures. They often want to direct their social interactions to certain people in order to start collaborations or to raise awareness about issues they support. However, users generally have scattered, unstructured information about the characteristics of their audiences, making it difficult for them to deliver the right messages or interactions to the right people. Existing audience-targeting tools allow people to select potential candidates based on predefined lists, but the tools provide few insights about whether or not these people would be appropriate for a specific type of communication. We introduce an online tool, Hax, to explore instead the idea of using interactive data visualizations to help people dynamically identify audiences for their different sharing efforts. We provide the results of a preliminary empirical evaluation that shows the strength of the idea and points to areas for future research.

Screen shots of Hax&rsquo;s social spread interface which lets users view the social groups of their potentially interested audiences

Visualizing Targeted Audiences

As scalable resolution display walls are becoming a common tool for visualizing and analyzing large amounts of data, many interaction techniques have been developed to explore information displayed on the wall. While the use of multi-touch has found widespread use in personal devices, limited work has been done exploring multi-touch interaction on scalable resolution display walls where multiple users can be simultaneously interacting with the display either collaboratively or independently. This thesis presents a multi-user interface designed to explore the potential of multi-touch on large scalable resolution display walls. This system allows multiple users to have access to the user interface anywhere across the display and search through collections of media files in a personal space. Finally this thesis will examine different layouts of the user interface and present the results of a user experience study to evaluate this multi-touch centric user interface design.


SAGETouchUI

Multi-User Interface for Scalable Resolution Touch Walls

The scale and complexity of today&rsquo;s datasets frequently overwhelm conventional visualization interfaces, which could negatively impact the quality of the visual analytic activity. In this paper, we investigate the use of Large, High-Resolution displays in exploratory visual analysis scenarios. We argue that the ability to see and interact with more information at once fundamentally affects users&rsquo; analytic behavior, prompting them to explore their data more broadly. This positive effect may also enhance the diversity of questions and hypotheses conceived and explored by users during their analysis. 

Keywords: Information visualization; visual exploration; visual analytics; large high-resolution displays

The visualization environment employed in the pilot user study

Expanding the Porthole: Leveraging Large, High-Resolution Displays in Exploratory Visual Analysis

Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse&rsquo;s acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

A screenshot of the HANDS interface enriched with clinical decision support features

Evaluating a clinical decision support interface for end-of-life nurse care

We present our experience ind esigning and testing a CDSS interface embedded in a nursing Electronic Healthcare Record (EHR) system. Our interface directed professional nurse clinicians towards an optimal care decision that was rarely performed in non-CDSS-assisted practice. We also show how decision making isa ffected by CDSS feature grouping and by the navigation strategy of nurses within the interface. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

The grouped interface puts all clinical decision support features in a single pop-up screen

Evaluating a Cinical Decision Support Interface For End-of-Life Nurse Care

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 work spaces 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&trade; system, and show how a Hybrid Reality Environment proved effective in supporting work for a co-located research group in the environmental sciences. 

Keywords: Multi-view, Tiled Displays, Cluster, Immersive Environments, Middleware

Omegalib immersive visualization running in the CAVE2, which is split into two workspaces to display additional 2D views

Omegalib: a Multi-View Application Framework for Hybrid Reality Display Environments

<a href="http://doi.acm.org/10.1145/2582051.2582072">http://doi.acm.org/10.1145/2582051.2582072</a> 

Recent research studies have shown the serious health risks associated with prolonged sitting. Standing up and walking on a regular basis has been proved to improve an office worker&rsquo;s well-being. Small behavioral changes like the aforementioned are the basis of preventive medicine and even though they appear easy to follow, in practice are difficult to apply. Advances in technology miniaturization and smart sensors are paving the way for the development of devices that empower preventive medicine. These devices use the power of persuasion to help people change behavior and maintain well-being. They act as an ambient personal &ldquo;coach&rdquo; that monitors and intervenes at the right time. In this paper we present the HealthBar, an ambient persuasive device that helps users break up their prolonged sitting habits. 

Keywords 
Human Augmentics; Ambient Displays; Persuasive Technologies; Calm Technologies; Context-Awareness; Preventive Healthcare

The HealthBar installed below the monitor of an office worker

The HealthBar: A Persuasive Ambient Display to improve the office worker&rsquo;s well being

Laser use in the medical field brought many enhancements to clinical and surgical procedures. Many different devices are now available for dental use. Lasers have sterilizing and coagulative effects that greatly reduce intra-operative bleeding, postoperative pain and inflammation, which in turn enhances the healing process and reduces tissue scarring significantly. 

The aim of this study is to compare the ability and quality of both Holmium and Biolase dental laser to induce bleeding control and coagulation of incisional wounds by measuring the extent of lateral tissue damage. 

Tissue Treatment: Four incisions were made in live porcine skin using a scalpel for each laser to be tested. One control incision was not exposed to laser treatment, and remaining incisions were treated with either the Holmium or Biolase dental laser. The tissues were then harvested for further processing. 

Standard IHC staining techniques were used with the BA-9020 Biotinylated, Anti-swine IgG (H+L) antibody (Vector Laboratories, Inc., Burlingame, CA). Damaged tissue appears purple. 

A Zeiss Axiovert 40 CFL inverted, digital light microscope (20X magnification) was used to digitize images. An Immunera Corp., InfinityX-32C, 32 megapixal CCD camera was used with image creation software for image capture. 

EVL&rsquo;s OmegaDesk was used to create 3D images to compare the extent of tissue damage. Lateral tissue damage caused by Holmium and Biolase dental laser was measured according the immunohistochemical staining technique which appears purple in color. The depth and the amount of lateral tissue damage were measured. Holmium showed a higher extent of tissue damage in comparison to Biolase which showed minimal tissue damage. 

Based on the evaluation techniques used, the Holmium laser is more efficient creating bleeding control and coagulation effects more than Biolase dental laser. 

Funding: United States Air Force Surgeon General&rsquo;s Office, Agreement #FA7014-09-2-0003

Tissue samples being analyzed on EVL&rsquo;s OmegaDesk

Immunohistochemical Evaluation of Bleeding Control Induced by Holmium Laser and Biolase Dental Laser As Coagulting Devices of Incisional Wounds

The proliferation of multi-touch, tabletop display systems during the last few years have made them an attractive option for interactive, multiuser applications such as museum exhibits and video games. While there is a large body of research on the use of multi-touch and tabletop devices in general purpose applications, far less research has investigated the use of these systems in video games and other entertainment applications. This paper provides a set of guidelines specific to multi-touch displays that can be used to augment existing video game development principles. Through example, we illustrate how the unique capabilities of multi-touch displays can be leveraged to create unique forms of gameplay that offer highly engaging multiplayer game experience. We describe three multiplayer games that have been developed by students as part of an interdisciplinary course in video game design. 

Keywords: Video Games, Multi-Touch, Multiplayer

Zombie Apocalypse Gameplay on EVL&rsquo;s TacTile Multi-touch Display

Design Guidelines for Multiplayer Video Games on Multi-touch Displays

This paper describes the design and pilot enactment of an instructional unit for elementary school students, Hunger Games, which centers on development of learner understandings of animal foraging behavior. Inspired by traditional teaching practices employing physical simulations, within the unit students engage in an embodied enactment of foraging using stuffed animals (with embedded RFID tags) as tangible avatars to represent their foraging among food patches (with camouflaged RFID readers) distributed around a classroom. Displays situated near the food patches provide students with information regarding the energy gain as the forage in the environment. A two-period pilot enactment of the unit demonstrated the feasibility of the design for classroom use, evidenced the development of affective relationships between learners and avatars, and afforded the emergence of unanticipated behaviors that promoted new questions about the science phenomena. The results suggest provisional support for the effectiveness of the unit as a science learning environment. 
Keywords: Indoor location, RFID, visualization, game theory, education, learning 
ISBN: 978-1-4503-2635-3

Students checking on their total energy gain over the course of a foraging bout.

Back to the Future: Embodied Classroom Simulations of Animal Foraging

In this paper, we propose an approach to improving the I/O performance of an IBM Blue Gene/Q supercomputing system using a novel framework that can be integrated into high performance applications. We take advantage of the systems&rsquo; tremendous computing resources and high interconnection bandwidth among compute nodes to efficiently exploit I/O bandwidth. This approach focuses on loss-less data compression, topology-aware data movement, and subfiling. The efficacy of this solution is demonstrated using micro-benchmarks and an application-level benchmark.

IBM Blue Gene/Q at Argonne National Laboratory

Scalable parallel I/O on a Blue Gene/Q supercomputer using compression, topology-aware data aggregation, and subfiling

This paper proposes a method that creates a multi-view interactive visualization that allows users to explore connections between garbage collection (GC) generated by Java Virtual Machine (JVM) and latency in applications used in financial transactions. With this tool users can explore large collections of GC and latency events, easily identify important events, and subsequently focus on the relationships and details of such events without losing the “big picture” perspective on the events as a whole. We discuss the impact of this tool on controlling the effects of GC on latency and variability in financial trades with an exchange. 
Keywords: Information Visualization, Time Series Data Visualization, Detail View, Gc Visualization, Latency, Performance, Trading System.

A screenshot of the GCLViz system.

GCLViz: Garbage Collection vs. Latency Visualization

Background: Mechanistic models that describe the dynamical behaviors of biochemical systems are common in computational systems biology, especially in the realm of cellular signaling. The development of families of such models, either by a single research group or by different groups working within the same area, presents significant challenges that range from identifying structural similarities and differences between models to understanding how these differences affect system dynamics. 
Methods: We present the development and features of an interactive model exploration system, MOSBIE, which provides utilities for identifying similarities and differences between models within a family. Models are clustered using a custom similarity metric, and a visual interface is provided that allows a researcher to interactively compare the structures of pairs of models as well as view simulation results. 
Results: We illustrate the usefulness of MOSBIE via two case studies in the cell signaling domain. We also present feedback provided by domain experts and discuss the benefis, as well as the limitations, of the approach. 
Keywords: visualization; visual computing; rule-based modeling; cell signaling

The TLR4 family of models. A similarity comparison between models TLR4 v15 and TLR4 RPS v1 in the TLR4 family.

MOSBIE: A Tool for Comparison and Analysis of Rule-Based Biochemical Models

In this chapter we summarize the top research challenges in creating successful visualization tools for tensor fields in engineering. The analysis is based on our collective experiences and on discussions with both domain experts and visualization practitioners. We find that creating visualization tools for engineering tensors often involves solving multiple different technical problems at the same
time - including visual intuitiveness, scalability, interactivity, providing both detail and context, integration with modeling and simulation, representing uncertainty and managing multi-fields; as well as overcoming terminology barriers and advancing research in the mathematical aspects of tensor field processing. We further note the need for tools and data repositories to encourage faster advances in the field. Our interest in creating and proposing this list is to initiate a discussion about important research issues within the visualization of engineering tensor fields.

Paraview rendering of the shock regions (points within 0.01 of the local speed/speed of sound ratio of 1) in a rich and very large – 21M-points – combustion dataset.