Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips
01 Dec 2013-IEEE Transactions on Visualization and Computer Graphics (IEEE)-Vol. 19, Iss: 12, pp 2149-2158
TL;DR: A new model is proposed that allows users to visually query taxi trips and is able to express a wide range of spatio-temporal queries, and it is flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results.
Abstract: As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision making and policies. In this paper, we focus on a particularly important urban data set: taxi trips. Taxis are valuable sensors and information associated with taxi trips can provide unprecedented insight into many different aspects of city life, from economic activity and human behavior to mobility patterns. But analyzing these data presents many challenges. The data are complex, containing geographical and temporal components in addition to multiple variables associated with each trip. Consequently, it is hard to specify exploratory queries and to perform comparative analyses (e.g., compare different regions over time). This problem is compounded due to the size of the data-there are on average 500,000 taxi trips each day in NYC. We propose a new model that allows users to visually query taxi trips. Besides standard analytics queries, the model supports origin-destination queries that enable the study of mobility across the city. We show that this model is able to express a wide range of spatio-temporal queries, and it is also flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results. We have built a scalable system that implements this model which supports interactive response times; makes use of an adaptive level-of-detail rendering strategy to generate clutter-free visualization for large results; and shows hidden details to the users in a summary through the use of overlay heat maps. We present a series of case studies motivated by traffic engineers and economists that show how our model and system enable domain experts to perform tasks that were previously unattainable for them.
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Cites methods from "Visual Exploration of Big Spatio-Te..."
...For example, translating New York City taxi trip data into urban visualization [261] and supporting traffic incident analysis [262]....
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Cites methods from "Visual Exploration of Big Spatio-Te..."
...Raw data must be processed for visualization and analysis....
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...Table I lists potential data sources and characteristics of available social signal data....
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References
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1,377 citations
"Visual Exploration of Big Spatio-Te..." refers methods in this paper
...Our implementation is based on a spacepartitioning data structure, k-d tree [11], that treats each taxi trip as a point in a k-dimensional space....
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...To support spatio-temporal queries at interactive rates, we have built a specialized index based on k-d trees [11] (Sec....
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TL;DR: Polaris is presented, an interface for exploring large multidimensional databases that extends the well-known pivot table interface that includes an interfaces for constructing visual specifications of table-based graphical displays and the ability to generate a precise set of relational queries from the visual specifications.
Abstract: In the last several years, large multidimensional databases have become common in a variety of applications, such as data warehousing and scientific computing. Analysis and exploration tasks place significant demands on the interfaces to these databases. Because of the size of the data sets, dense graphical representations are more effective for exploration than spreadsheets and charts. Furthermore, because of the exploratory nature of the analysis, it must be possible for the analysts to change visualizations rapidly as they pursue a cycle involving first hypothesis and then experimentation. In this paper, we present Polaris, an interface for exploring large multidimensional databases that extends the well-known pivot table interface. The novel features of Polaris include an interface for constructing visual specifications of table-based graphical displays and the ability to generate a precise set of relational queries from the visual specifications. The visual specifications can be rapidly and incrementally developed, giving the analyst visual feedback as he constructs complex queries and visualizations.
711 citations
"Visual Exploration of Big Spatio-Te..." refers background in this paper
...Another notable effort in this direction is the Polaris system [33] and its successor, Tableau....
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TL;DR: In this article, a Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields is presented.
Abstract: The study of spatiotemporal dynamics is certainly not new, nor is it unique to the field of geography. Nevertheless, addressing complex human and environmental issues such as global warming and human impacts on the environment requires empirical examination from a much broader and integrated perspective than can be accomplished with current techniques. Although Geographic Information Systems (GIS) are intended to provide an integrated and flexible tool for analyzing large volumes of data, they are historically geared toward the representation and analysis of situations frozen in time. Efforts to enhance the temporal capabilities of GIS have served to reveal many problems at a fundamental conceptual level. In order to address this problem, this paper presents a new Triad representational approach that unifies temporal-as well as locational-and object-related aspects and that incorporates concepts from perceptual psychology, artifical intelligence, and other fields. The goal of this research is a d...
681 citations
"Visual Exploration of Big Spatio-Te..." refers background or methods in this paper
...We show that this model supports a wide range of queries, and in particular, the three classes of queries in Peuquet’s typology [29]: identify a set of objects at a given location and time; given a time and a set of objects, describe the locations occupied by the objects; and describe the times a set of objects occupied a given set of locations....
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...4, the system supports the query types defined in the Triad Framework [29]....
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...In particular, it supports queries types in Peuquet’s Triad Framework [29]....
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TL;DR: A new concept for direct manipulation of databases, called dynamic queries, that allows users to formulate queries with graphical widgets, such as sliders, is designed, implemented and evaluated.
Abstract: We designed, implemented and evaluated a new concept for direct manipulation of databases, called dynamic queries, that allows users to formulate queries with graphical widgets, such as sliders. By providing a graphical visualization of the database and search results, users can find trends and exceptions easily. Eighteen undergraduate chemistry students performed statistically significantly faster using a dynamic queries interface compared to two interfaces both providing form fill-in as input method, one with graphical visualization output and one with all-textual output. The interfaces were used to explore the periodic table of elements and search on their properties.
550 citations
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...[2] introduced the concept of dynamic queries, where queries are specified through graphical widgets....
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TL;DR: A structured inventory of existing exploratory techniques related to the types of data and tasks they are appropriate for is considered, which is potentially helpful for data analysts—users of geovisualization tools.
Abstract: Current software tools for visualization of spatio-temporal data, on the one hand, utilize the opportunities provided by modern computer technologies, on the other hand, incorporate the legacy from the conventional cartography. We have considered existing visualization-based techniques for exploratory analysis of spatio-temporal data from two perspectives: (1) what types of spatio-temporal data they are applicable to; (2) what exploratory tasks they can potentially support. The technique investigation has been based on an operational typology of spatio-temporal data and analytical tasks we specially devised for this purpose. The result of the study is a structured inventory of existing exploratory techniques related to the types of data and tasks they are appropriate for. This result is potentially helpful for data analysts—users of geovisualization tools: it provides guidelines for selection of proper exploratory techniques depending on the characteristics of data to analyze and the goals of analysis. At the same time the inventory as well as the suggested typology of tasks could be useful for tool designers and developers of various domain-specific geovisualization applications. The designers can, on the one hand, see what task types are insufficiently supported by the existing tools and direct their creative activities towards filling the gaps, on the other hand, use the techniques described as basic elements for building new, more sophisticated ones. The application developers can, on the one hand, use the task and data typology in the analysis of potential user needs, on the other hand, appropriately select and combine existing tools in order to satisfy these needs.
419 citations