Reconciling big data and thick data to advance the new urban science and smart city governance

被引:10
作者
Hong, Andy [1 ,2 ]
Baker, Lucy [2 ]
Curiel, Rafael Prieto [3 ]
Duminy, James [4 ,5 ]
Buswala, Bhawani [2 ]
Guan, ChengHe [6 ]
Ravindranath, Divya [7 ]
机构
[1] Univ Utah, Salt Lake City, UT 84112 USA
[2] Univ Oxford, Oxford, England
[3] UCL, London, England
[4] Univ Bristol, Bristol, Avon, England
[5] Univ Cape Town, Cape Town, South Africa
[6] New York Univ Shanghai, Shanghai, Peoples R China
[7] Indian Inst Human Settlements, Bengaluru, India
关键词
Big data; thick data; urban science; smart cities; road safety; ethnography; TRAFFIC ACCIDENTS; ROAD SAFETY; SOCIAL MEDIA; RISK; IDENTIFICATION; PERCEPTIONS; FUTURE; CITIES; DATAFICATION; ETHNOGRAPHY;
D O I
10.1080/07352166.2021.2021085
中图分类号
TU98 [区域规划、城乡规划];
学科分类号
0814 ; 082803 ; 0833 ;
摘要
Amid growing enthusiasm for a "new urban science" and "smart city" approaches to urban management, "big data" is expected to create radical new opportunities for urban research and practice. Meanwhile, anthropologists, sociologists, and human geographers, among others, generate highly contextualized and nuanced data, sometimes referred to as 'thick data,' that can potentially complement, refine and calibrate big data analytics while generating new interpretations of the city through diverse forms of reasoning. While researchers in a range of fields have begun to consider such questions, scholars of urban affairs have not yet engaged in these discussions. The article explores how ethnographic research could be reconciled with big data-driven inquiry into urban phenomena. We orient our critical reflections around an illustrative example: road safety in Mexico City. We argue that big and thick data can be reconciled in and through three stages of the research process: research formulation, data collection and analysis, and research output and knowledge representation.
引用
收藏
页码:1737 / 1761
页数:25
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