Eric Sauda

Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships

Numerous systems have been developed to display large collections of data for urban contexts; however, most have focused on layering of single dimensions of data and manual calculations to understand relationships within the urban environment. Furthermore, these systems often limit the users perspectives on the data, thereby diminishing the users spatial understanding of the viewing region. In this paper, we introduce a highly interactive urban visualization tool that provides intuitive understanding of the urban data. Our system utilizes an aggregation method that combines buildings and city blocks into legible clusters, thus providing continuous levels of abstraction while preserving the users mental model of the city. In conjunction with a 3D view of the urban model, a separate but integrated information visualization view displays multiple disparate dimensions of the urban data, allowing the user to understand the urban environment both spatially and cognitively in one glance. For our evaluation, expert users from various backgrounds viewed a real city model with census data and confirmed that our system allowed them to gain more intuitive and deeper understanding of the urban model from different perspectives and levels of abstraction than existing commercial urban visualization systems.

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.

Revaluating urban space through tweets: An analysis of Twitter-based mobile food vendors and online communication

The rise of mobile food vending in US cities combines urban space and mobility with continuous online communication. Unlike traditional urban spaces that are predictable and known, contemporary vendors use information technology to generate impromptu social settings in unconventional and often underutilized spaces. This unique condition requires new methods that interpret online communication as a critical component in the production of new forms of public life. We suggest qualitative approaches combined with data-driven analyses are necessary when planning for emergent behavior. In Charlotte, NC, we investigate the daily operations, tweet content, and spatial and temporal sequencing of six vendors over an extended period of time. The study illustrates the interrelationship between data, urban space, and time and finds that a significant proportion of tweet content is used to announce vending locations in a time-based pattern and that the spatial construction of events is often independent of traditional urban form.

GPS and road map navigation: the case for a spatial framework for semantic information

Urban environments require cognitive abilities focused on both spatial overview and detailed understanding of uses and places. These abilities are distinct but overlap and reinforce each other. Our work quantitatively and qualitatively measures the effects on a users overall understanding of the environment after navigating with either a GPS or a road map in a previously unknown neighborhood. Experimental recall of spatial and semantic information indicates that using a road map enables subjects to demonstrate a significantly better spatial understanding, identify semantic elements more often using common terms, place semantic elements in spatial locations with greater accuracy and recall semantic elements in tighter clusters than when using a GPS. We conclude that a spatial understanding is a necessary framework for organizing semantic information that is useful for inferred tasks.

The Whole Story: Building the Complete History of a Place

In this paper, we discuss how one can build a visual analytics system to comprehensively describe a place throughout its many interconnected histories. We discuss the needed 4D data structure, the analytics techniques, and the interactive visualizations. This combination of automated and interactive techniques can be brought together into a new, powerful capability. We focus on the example of Rome and, more specifically, on its architectural/cultural history.

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.

Data and Design: Using Knowledge Generation/Visual Analytic Paradigms to Understand Mobile Social Media in Urban Design

Architects and designers have recently become interested in the use of “big data”. The most common paradigm guiding this work is the optimization of a limited number of factors, e.g. facade designs maximizing light distribution. For most design problems, however, such optimization is oversimplified and reductive; the goal of design is the discovery of possibilities in conditions of complexity and uncertainty. This paper studies the use of Twitter as an extended case study for uncovering different methods for the analysis of urban social data, concluding that a visual analytic system that uses a knowledge generation approach is the best option to flexibly and effectively explore and understand large multidimensional urban datasets.

Urban Space Explorer: A Visual Analytics System for Urban Planning

Understanding people’s behavior is fundamental to many planning professions (including transportation, community development, economic development, and urban design) that rely on data about frequently traveled routes, places, and social and cultural practices. Based on the results of a practitioner survey, the authors designed Urban Space Explorer, a visual analytics system that utilizes mobile social media to enable interactive exploration of public-space-related activity along spatial, temporal, and semantic dimensions.

Keeping an Eye Out: Real Time, Real World Modeling of Behavior in Health Care Settings

Imagine a health care facility that is able to track and understand the meaningful behaviors of the patients 24 h a day, 365 days a year, understanding individual variation in behavior over both the short and the long term. Now consider the needs of patients with Alzheimers, who typically have trouble with spatial and visual issues. They are sometimes unable to distinguish between a shadow cast on the floor and a step; they can also spend the entire day at the “front door” anticipating arrivals and departures. The families of these patients, to the best of their ability, want to be able to maintain surveillance and understand the changes in the behavior of their parents or spouses. Continuing on the work of the Computing in Place research group that includes faculty with specialties in architecture, computer vision, ubiquitous computing and anthropology, we propose in this paper a new paradigm for intelligent architectural settings. Health care settings, like most architecture, are generally conceptualized as a spatial volume containing human and technical elements. There is an implicit distinction between the active contents and the passive container. From our research group’s expertise in ethnography, we emphasize the importance of meaning to the understanding of behavior, to the idea of place as a construed setting: or, as Clifford Geertz describes it, the difference between “a wink and a blink”. Our new paradigm proposes the creation of “intelligent” architectural settings that capture such meaningful behavior in real time and generate knowledge that is useful both in the real world and in the evaluation of design revisions.

Theatre of embedded intelligence

Computer visualization and user interface design has focused on the use of computers in expanded settings and the extension of the user interface. Our research investigates computer interfaces for incorporation into live performances. We have identified some feasible alternatives using motion & gesture capture, real-time audio and video compositing as well as creating methods for giving the actor specific control over computer controlled devices, making the computer a physical actor on stage. We have been creating prototypes of interactive computer environments during the semester to act as tests. We will be implementing the design of the selected components for the play Go Dog Go in the 2006/7 season.