Visual exploration of Location-Based Social Networks data in urban planning

D. F. Prieto, Eva Hagen, D. Engel, Dirk Bayer, J. T. Hernández, C. Garth, Inga Scheler
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引用次数: 8

Abstract

The increasing amount of data generated by Location Based Social Networks (LBSN) such as Twitter, Flickr, or Foursquare, is currently drawing the attention of urban planners, as it is a new source of data that contains valuable information about the behavior of the inhabitants of a city. Making this data accessible to the urban planning domain can add value to the decision making processes. However, the analysis of the spatial and temporal characteristics of this data in the context of urban planning is an ongoing research problem. This paper describes ongoing work in the design and development of a visual exploration tool to facilitate this task. The proposed design provides an approach towards the integration of a visual exploration tool and the capabilities of a visual query system from a multilevel perspective (e.g., multiple spatial scales and temporal resolutions implicit in LBSN data). A preliminary discussion about the design and the potential insights that can be gained from the exploration and analysis of this data with the proposed tool is presented, along with the conclusions and future work for the continuation of this work.
基于位置的社交网络数据在城市规划中的可视化探索
基于位置的社交网络(Location Based Social Networks, LBSN)如Twitter、Flickr或Foursquare产生的数据量不断增加,目前正引起城市规划者的注意,因为它是一种新的数据来源,包含有关城市居民行为的有价值信息。使城市规划领域能够访问这些数据可以为决策过程增加价值。然而,在城市规划的背景下分析这些数据的时空特征是一个正在进行的研究问题。本文描述了正在进行的设计和开发可视化探索工具的工作,以促进这项任务。提出的设计提供了一种从多层角度(例如,LBSN数据中隐含的多个空间尺度和时间分辨率)集成视觉探索工具和视觉查询系统功能的方法。本文提出了关于设计的初步讨论,以及可以从使用建议的工具对这些数据进行探索和分析中获得的潜在见解,以及结论和继续这项工作的未来工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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