11th EAEA Envisioning Architecture: Design, Evaluation, Communication Conference in 2013

Track 3 | Conceptual Representation | Exploring the layout of the built environment

Interactive urban analytics: time, place & data

ABSTRACT

The emerging field of visual analytics offers powerful new tools with which to understand complex built environments. In this paper, we demonstrate how to apply these interactive techniques to both temporal and spatial data in cities, using Rome, Italy, with its many interconnected histories, as a case study.
The technologies comprising temporal visual analytics create an intertwined history. Such a history begins with an overarching temporal narrative of the entire historical record of important events. We define ‘event’ as a meaningful occurrence at a particular place and time. An event in weather history could be a great storm, while one in religious history could be the building of a church. An intertwined history places events from various histories into the same time structure. We have chosen Rome because of its long history, abundant scholarship and overlapping geographies. Our methods include:

• Identification of events and sub-events and arrangement into hierarchical tree-structures.
• Correlation with GIS-based spatial structure.
• Derivation of meaningful topics from collection of written documents using the Stanford Modeling Toolbox.
• Generation of time based ‘scaffoldings’ as event outlines. • Collection of imagery based on maps, engravings, photographs, and automatic extraction of architectural imagery from perspectives.
• Use of Theme River and Event Identification visualizations.
• Design of interactive multi-view visualizations.

Visual analytic interfaces such as the one that we demonstrate have several important features that advance their usefulness.

1. Data is displayed in multiple windows using different forms of analysis. These windows are linked in such a way that data highlighted in one representation is simultaneously shown in multiple iterations.
2. Changes in the viewpoint in any window can allow a user to explore the data interactively. This means that a user can explore the data, coupling the computational capacities of the computer with the human ability to perceive patterns and meaning.
3. Analytic techniques allow the presentation of potential clusters of information to the user. Rather than operating upon a static archive, these techniques allow for possible conjectures of knowledge embedded within the huge silos of data.

PDF

AUTHORS

Jeffrey Balmer

School of Architecture, University of North Carolina, Charlotte; USA

Head of the Computer Aided Design Unit at the Institute of Architecture and Urban Planning, Lodz University of Technology. A member of the program council and a lecturer of the Postgraduate Studies in Conservation of Historic Built Structures at the Lodz University of Technology. In 2004 she defended a doctoral thesis "A model proposal for digitisation and recording data on architectural heritage in Poland based on European guidelines and best practices" at the University of Strathclyde in Glasgow. At the National Heritage Board of Poland she served as Representative Director for the Implementation of National Heritage Database, acted in the council for the implementation of the INSPIRE Directive in Poland and also acquired and coordinated a project CARARE funded under FP7.

Wenwen Dou

Department of Computer Science, University of North Carolina, Charlotte; USA

William Ribarsky

Department of Computer Science, University of North Carolina, Charlotte; USA

Eric Sauda

Digital Arts Center, School of Architecture, University of North Carolina, Charlotte; USA

index  |   11th conference website  |  EAEA website