There’s More Than One Kind of “Smart”: Big Data, Affect and Empathy in the City

This paper examines how mass ridership data can help describe cities from the bikers' perspective. We explore the possibility of using the data to reveal general bikeability patterns in 202 major Chinese cities. This process is conducted by constructing a bikeability rating system, the Mobike Riding Index (MRI), to measure bikeability in terms of usage frequency and the built environment. We first investigated mass ridership data and relevant supporting data; we then established the MRI framework and calculated MRI scores accordingly. This study finds that people tend to ride shared bikes at speeds close to 10 km/h for an average distance of 2 km roughly three times a day. The MRI results show that at the street level, the weekday and weekend MRI distributions are analogous, with an average score of 49.8 (range 0–100). At the township level, high-scoring townships are those close to the city centre; at the city level, the MRI is unevenly distributed, with high-MRI cities along the southern coastline or in the middle inland area. These patterns have policy implications for urban planners and policy-makers. This is the first and largest-scale study to incorporate mobile bike-share data into bikeability measurements, thus laying the groundwork for further research.

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Understanding policing demand and deployment through the lens of the city and with the application of big data

Urban Studies ◽

10.1177/0042098020981007 ◽

2021 ◽

pp. 004209802098100

Author(s):

Mark Ellison ◽

Jon Bannister ◽

Won Do Lee ◽

Muhammad Salman Haleem

Keyword(s):

Big Data ◽

Urban Environment ◽

Urban Areas ◽

Multilevel Model ◽

Open Data ◽

Front Line ◽

Criminological Research ◽

The Social ◽

Generalised Method Of Moments ◽

The City

The effective, efficient and equitable policing of urban areas rests on an appreciation of the qualities and scale of, as well as the factors shaping, demand. It also requires an appreciation of the factors shaping the resources deployed in their address. To this end, this article probes the extent to which policing demand (crime, anti-social behaviour, public safety and welfare) and deployment (front-line resource) are similarly conditioned by the social and physical urban environment, and by incident complexity. The prospect of exploring policing demand, deployment and their interplay is opened through the utilisation of big data and artificial intelligence and their integration with administrative and open data sources in a generalised method of moments (GMM) multilevel model. The research finds that policing demand and deployment hold varying and time-sensitive association with features of the urban environment. Moreover, we find that the complexities embedded in policing demands serve to shape both the cumulative and marginal resources expended in their address. Beyond their substantive policy relevance, these findings serve to open new avenues for urban criminological research centred on the consideration of the interplay between policing demand and deployment.

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Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽

10.1177/00420980211014026 ◽

2021 ◽

pp. 004209802110140

Author(s):

Sarah Barns

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Computational Models ◽

Data Driven ◽

Urban Systems ◽

Out Of The Loop ◽

Urban Futures ◽

Urban Behaviour ◽

The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

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Research on the demand for reference legal systems in Russia using Power BI

Informacionno-technologicheskij vestnik ◽

10.21499/2409-1650-2021-27-1-135-142 ◽

2021 ◽

pp. 135-142

Author(s):

Н.И. Царькова ◽

А.Н. Тарасов

Keyword(s):

Big Data ◽

Legal Systems ◽

Number Of Customers ◽

The City

Основная цель статьи состоит в обработке больших данных, генерируемых компаниями, разрабатывающие справочные правовые системы. Задача заключается в визуализации количества клиентов, сегментированных по городам для исследования распространённости справочных правовых систем в регионе. В качестве инструмента обработки больших данных и визуализации полученных итогов используется продукт компании Microsoft - Power BI. Авторы анализируют уникальные значения количества клиентов, в зависимости от города и выявляют регионы с наименьшим количеством пользователей. В заключении были подведены итоги исследования и разработаны планы на дальнейшую работу с использованием полученных результатов. The main purpose of the article is to process big data generated by companies that develop reference legal systems. The task is to visualize the number of clients segmented by city to study the prevalence of reference legal systems in the region. Microsoft's Power BI product is used as a tool for processing big data and visualizing the results. The authors analyze the unique values of the number of customers, depending on the city, and identify the regions with the lowest number of users. In conclusion, the results of the study were summarized and plans were developed for further work using the results obtained.

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Enterprise service bus architecture for the big data systems

Management and Production Engineering Review ◽

10.2478/mper-2014-0004 ◽

2014 ◽

Vol 5 (1) ◽

pp. 28-31 ◽

Cited By ~ 1

Author(s):

Cezary Orłowski ◽

Edward Szczerbicki ◽

Jan Grabowski

Keyword(s):

Big Data ◽

Data Systems ◽

Flow Mechanism ◽

Enterprise Service Bus ◽

City Hall ◽

Decision Making System ◽

Processing Resources ◽

Big Data Systems ◽

Bus Architecture ◽

The City

Abstract This paper presents the construction of the enterprise service bus architecture in data processing resources for a big data decision-making system for the City Hall in Gdansk. The first part presents the key processes of bus developing: the installation of developing environment, the database connection, the flow mechanism and data presentation. Developing processes were supported by models: KPI (Key Processes Identifier) and SOP (Simple Operating Procedures) (also connected to the bus). The summary indicates the problems of the bus construction, especially processes of routing, conversion, and handling events.

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Big data and the city

Handbook of Urban Geography ◽

10.4337/9781785364600.00013 ◽

2019 ◽

pp. 63-75

Author(s):

Matthew Zook

Keyword(s):

Big Data ◽

The City

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Managing Large Amounts of Data Generated by a Smart City Internet of Things Deployment

International Journal on Semantic Web and Information Systems ◽

10.4018/ijswis.2016100102 ◽

2016 ◽

Vol 12 (4) ◽

pp. 22-42 ◽

Cited By ~ 17

Author(s):

Jorge Lanza ◽

Pablo Sotres ◽

Luis Sánchez ◽

Jose Antonio Galache ◽

Juan Ramón Santana ◽

...

Keyword(s):

Big Data ◽

Internet Of Things ◽

Information And Communication Technologies ◽

Smart City ◽

Smart Cities ◽

Communication Technologies ◽

Added Value ◽

Amount Of Information ◽

Information And Communication ◽

The City

The Smart City concept is being developed from a lot of different axes encompassing multiple areas of social and technical sciences. However, something that is common to all these approaches is the central role that the capacity of sharing information has. Hence, Information and Communication Technologies (ICT) are seen as key enablers for the transformation of urban regions into Smart Cities. Two of these technologies, namely Internet of Things and Big Data, have a predominant position among them. The capacity to “sense the city” and access all this information and provide added-value services based on knowledge derived from it are critical to achieving the Smart City vision. This paper reports on the specification and implementation of a software platform enabling the management and exposure of the large amount of information that is continuously generated by the IoT deployment in the city of Santander.

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Comparisons of the City Brand Influence of Global Cities: Word-Embedding Based Semantic Mining and Clustering Analysis on the Big Data of GDELT Global News Knowledge Graph

Sustainability ◽

10.3390/su12166294 ◽

2020 ◽

Vol 12 (16) ◽

pp. 6294

Author(s):

Chenyu Zheng

Keyword(s):

Big Data ◽

News Media ◽

Clustering Analysis ◽

Global City ◽

Word Embedding ◽

Knowledge Graph ◽

Global Cities ◽

City Brand ◽

Semantic Mining ◽

The City

Global cities act as influential hubs in the networked world. Their city brands, which are projected by the global news media, are becoming sustainable resources in various global competitions and cooperations. This study adopts the research paradigm of computational social science to assess and compare the city brand attention, positivity, and influence of ten Globalization and World Cities Research Network (GaWC) Alpha+ global cities, along with their dimensional structures, based on combining the cognitive and affective theoretical perspectives on the frameworks of the Anholt global city brand dimension system, the big data of global news knowledge graph in Google’s Global Database of Events, Language, and Tone (GDELT), and the technologies of word-embedding semantic mining and clustering analysis. The empirical results show that the overall values and dimensional structures of city brand influence of global cities form distinct levels and clusters, respectively. Although global cities share a common structural characteristic of city brand influence of the dimensions of presence and potential being most prominent, Western and Eastern global cities differentiate in the clustering of dimensional structures of city brand attention, positivity, and influence. City brand attention is more important than city brand positivity in improving the city brand influence of global cities. The preferences of the global news media over global city brands fits the nature of global cities.

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