文章基本信息

标题：Riding from Urban Data to Insight Using New York City Taxis
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作者：Juliana Freire ; Cl醬dio Silva ; Huy Vo 等
期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2015
卷号：37
期号：4
出版社：IEEE Computer Society
摘要：About half of humanity lives in urban environments today and that number will grow to 80% by themiddle of this century. Cities are thus the loci of resource consumption, of economic activity, and ofinnovation. Given our increasing ability to collect, transmit, store, and analyze data, there is a greatopportunity to better understand cities, and enable them to deliver services efficiently and sustainablywhile keeping their citizens safe, healthy, prosperous, and well-informed. But making sense of all thedata available is hard. Currently, urban data exploration is often limited to confirmatory analyses con-sisting of batch-oriented queries and the exploration of well-defined questions over specific regions.The lack of interactivity makes this process both time-consuming and cumbersome. This problem iscompounded in the presence of big, multivariate spatio-temporal data, which is ubiquitous in urbanenvironments. Another challenge comes from the need to empower social scientists, policy makes andurban residents who lack computer science expertise to leverage these data. In this paper, we give anoverview of our recent work on techniques that combine data management and visualization to enable abroad set of users to interactively explore large, spatio-temporal data. We describe a visual query inter-face that simplifies the process of specifying spatio-temporal queries as well as new indexing techniquethat enables these queries to be evaluated at interactive rates. We also present a scalable framework thatapplies computational topology to automatically find interesting data slices so as to help guide users inthe exploratory process.