DocumentCode :
22295
Title :
Using Topological Analysis to Support Event-Guided Exploration in Urban Data
Author :
Doraiswamy, Harish ; Ferreira, Nuno ; Damoulas, Theodoros ; Freire, Juliana ; Silva, Claudio T.
Author_Institution :
New York Univ., New York, NY, USA
Volume :
20
Issue :
12
fYear :
2014
fDate :
Dec. 31 2014
Firstpage :
2634
Lastpage :
2643
Abstract :
The explosion in the volume of data about urban environments has opened up opportunities to inform both policy and administration and thereby help governments improve the lives of their citizens, increase the efficiency of public services, and reduce the environmental harms of development. However, cities are complex systems and exploring the data they generate is challenging. The interaction between the various components in a city creates complex dynamics where interesting facts occur at multiple scales, requiring users to inspect a large number of data slices over time and space. Manual exploration of these slices is ineffective, time consuming, and in many cases impractical. In this paper, we propose a technique that supports event-guided exploration of large, spatio-temporal urban data. We model the data as time-varying scalar functions and use computational topology to automatically identify events in different data slices. To handle a potentially large number of events, we develop an algorithm to group and index them, thus allowing users to interactively explore and query event patterns on the fly. A visual exploration interface helps guide users towards data slices that display interesting events and trends. We demonstrate the effectiveness of our technique on two different data sets from New York City (NYC): data about taxi trips and subway service. We also report on the feedback we received from analysts at different NYC agencies.
Keywords :
government data processing; NYC; New York City; complex dynamics; computational topology; data slices; governments; manual exploration; multiple scales; public services; subway service; support event guided exploration; taxi trips; time-varying scalar functions; topological analysis; urban data; visual exploration interface; Cities and towns; Data visualization; Event detection; Roads; Terrain mapping; Topology; Vegetation; Computational topology; event detection; spatio-temporal index; urban data; visual exploration;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2014.2346449
Filename :
6876004
Link To Document :
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