Isaac Cho

VAiRoma: A Visual Analytics System for Making Sense of Places, Times, and Events in Roman History

Learning and gaining knowledge of Roman history is an area of interest for students and citizens at large. This is an example of a subject with great sweep (with many interrelated sub-topics over, in this case, a 3,000 year history) that is hard to grasp by any individual and, in its full detail, is not available as a coherent story. In this paper, we propose a visual analytics approach to construct a data driven view of Roman history based on a large collection of Wikipedia articles. Extracting and enabling the discovery of useful knowledge on events, places, times, and their connections from large amounts of textual data has always been a challenging task. To this aim, we introduce VAiRoma, a visual analytics system that couples state-of-the-art text analysis methods with an intuitive visual interface to help users make sense of events, places, times, and more importantly, the relationships between them. VAiRoma goes beyond textual content exploration, as it permits users to compare, make connections, and externalize the findings all within the visual interface. As a result, VAiRoma allows users to learn and create new knowledge regarding Roman history in an informed way. We evaluated VAiRoma with 16 participants through a user study, with the task being to learn about roman piazzas through finding relevant articles and new relationships. Our study results showed that the VAiRoma system enables the participants to find more relevant articles and connections compared to Web searches and literature search conducted in a roman library. Subjective feedback on VAiRoma was also very positive. In addition, we ran two case studies that demonstrate how VAiRoma can be used for deeper analysis, permitting the rapid discovery and analysis of a small number of key documents even when the original collection contains hundreds of thousands of documents.

A survey on visual analysis approaches for financial data

Market participants and businesses have made tremendous efforts to make the best decisions in a timely manner under varying economic and business circumstances. As such, decision‐making processes based on Financial data have been a popular topic in industries. However, analyzing Financial data is a non‐trivial task due to large volume, diversity and complexity, and this has led to rapid research and development of visualizations and visual analytics systems for Financial data exploration. Often, the development of such systems requires researchers to collaborate with Financial domain experts to better extract requirements and challenges in their tasks. Work to systematically study and gather the task requirements and to acquire an overview of existing visualizations and visual analytics systems that have been applied in Financial domains with respect to real‐world data sets has not been completed. To this end, we perform a comprehensive survey of visualizations and visual analytics. In this work, we categorize Financial systems in terms of data sources, applied automated techniques, visualization techniques, interaction, and evaluation methods. For the categorization and characterization, we utilize existing taxonomies of visualization and interaction. In addition, we present task requirements extracted from interviews with domain experts in order to help researchers design better systems with detailed goals.

Evaluation of a bimanual simultaneous 7DOF interaction technique in virtual environments

This paper introduces our novel bimanual interaction technique, Spindle+Wheel that provides simultaneous 7DOF. Spindle+Wheel takes advantage of greater finger dexterity, the “bandwidth-of-the-fingers” and passive haptics, by using a pair of precision-grasp 6DOF isotonic input devices rather than using either a tracked pair of pinch gloves or a pair of power-grasped 6DOF isotonic input devices. Two user studies were conducted to show that our simultaneous 7DOF interaction technique outperforms a previous two-handed technique as well as a one-handed scene-in-hand technique for a 7DOF travel task.

Evaluating dynamic-adjustment of stereo view parameters in a multi-scale virtual environment

Dynamic view parameter adjustment can reduce visual fatigue issues in stereo displays. In a multi-scale virtual environment, which has geometric details ranging over several orders of magnitude, these adjustments are particularly important. We evaluate how two adjustment techniques interact with 7 degree-of-freedom navigation in desktop VR and a CAVE. The travel task has two stages, an initial targeted zoom and detailed geometric inspection. The results show benefits of the adjustments both for reducing fusion problems and for task completion time, but only in certain condition combinations. Peculiar view configuration examples show the difficulty of creating robust adjustment rules.

Comparison of Device-Based, One and Two-Handed 7DOF Manipulation Techniques

We evaluate three bimanual 7 degree-of-freedom (7DOF) object manipulation techniques that use a pair of precision grasped isotonic devices called buttonballs. 7DOF manipulation means changing position, orientation and scale. We compare the techniques in a (stereo) Fish-tank Virtual Reality (VR) system. The user study displays multiple randomly located boxes of different sizes and the user must dock (i.e. align) each target box with an objective box at the screen center. Comparing task completion times shows that in cases where target and objective boxes are the same size, all three techniques perform equivalently. When the sizes differ--requiring a scale change--two of the techniques, Spindle+Wheel and a minor variant of Grab-and-Scale perform similarly, and are both faster than the third technique, One-Hand+Scale. We compare and contrast our results with other work including free-hand versus held device input and also with 7DOF object manipulation versus 7DOF view manipulation.

Evaluation of 3D virtual cursor offset techniques for navigation tasks in a multi-display virtual environment

Extending the position of a 3D virtual cursor that represents the location of a physical tracking input device in the virtual world often enhances efficiency and usability of 3D user interactions. Most previous studies, however, tend to focus on evaluating cursor offset techniques for specific types of interactions, mainly object selection and manipulation. Furthermore, not many studies address cursor offset techniques for multi-display virtual environments, such as a Cave Automatic Virtual Environment (CAVE), which require different directions of the cursor offset for different displays. This paper presents two formal user studies that evaluate effects of varying offset techniques on navigation tasks in a CAVE system. The first study compares four offset techniques: no offset, fixed-length offset, nonlinear offset and linear offset. The results indicate that the linear offset technique outperforms other techniques for exocentric travel tasks. The second study investigates the influence of three different offset lengths in the linear offset technique on the same task.

Space-Time Kernel Density Estimation for Real-Time Interactive Visual Analytics

We present a GPU-based implementation of the Space-Time Kernel Density Estimation (STKDE) that provides massive speed up in analyzing spatialtemporal data. In our work we are able to achieve subsecond performance for data sizes transferable over the Internet in realistic time. We have integrated this into web-based visual interactive analytics tools for analyzing spatial-temporal data. The resulting integrated visual analytics (VA) system permits new analyses of spatial-temporal data from a variety of sources. Novel, interlinked interface elements permit efficient, meaningful analyses.

Urban Activity Explorer: Visual Analytics and Planning Support Systems

Urban Activity Explorer is a new prototype for a planning support system that uses visual analytics to understand mobile social media data. Mobile social media data are growing at an astounding rate and have been studied from a variety of perspectives. Our system consists of linked visualizations that include temporal, spatial and topical data, and is well suited for exploring multiple scenarios. It allows a wide latitude for exploration, verification and knowledge generation as a central feature of the system. For this work, we used a database of approximately 1,000,000 geolocated tweets over a two-month period in Los Angeles. Urban Activity Explorer’s usage of visual analytic principles is uniquely suited to address the issues of inflexibility in data systems that led to planning support systems. We demonstrate that mobile social media can be a valuable and complementary source of information about the city.

Stereo and motion cues effect on depth perception of volumetric data

Displays supporting stereoscopic and head-coupled motion parallax can enhance human perception of containing 3D surfaces and 3D networks but less for so volumetric data. Volumetric data is characterized by a heavy presence of transparency, occlusion and highly ambiguous spatial structure. There are many different rendering and visualization algorithms and interactive techniques that enhance perception of volume data and these techniques‟ effectiveness have been evaluated. However, how VR display technologies affect perception of volume data is less well studied. Therefore, we conduct two formal experiments on how various display conditions affect a participant‟s depth perception accuracy of a volumetric dataset. Our results show effects of VR displays for human depth perception accuracy for volumetric data. We discuss the implications of these finding for designing volumetric data visualization tools that use VR displays. In addition, we compare our result to previous works on 3D networks and discuss possible reasons for and implications of the different results.

HyFinBall: a two-handed, hybrid 2D/3D desktop VR interface for multi-dimensional visualization

This paper presents the concept, working prototype and design space of a two-handed, hybrid spatial user interface for minimally immersive desktop VR targeted at multi-dimensional visualizations. The user interface supports dual button balls (6DOF isotonic controllers with multiple buttons) which automatically switch between 6DOF mode (xyz + yaw,pitch,roll) and planar-3DOF mode (xy + yaw) upon contacting the desktop. The mode switch automatically switches a button ball’s visual representation between a 3D cursor and a mouse-like 2D cursor while also switching the available user interaction techniques (ITs) between 3D and 2D ITs. Further, the small form factor of the button ball allows the user to engage in 2D multi-touch or 3D gestures without releasing and re-acquiring the device. We call the device and hybrid interface the HyFinBall interface which is an abbreviation for ‘Hybrid Finger Ball.’ We describe the user interface (hardware and software), the design space, as well as preliminary results of a formal user study. This is done in the context of a rich, visual analytics interface containing coordinated views with 2D and 3D visualizations and interactions