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. 2015 Oct 27:2:150055.
doi: 10.1038/sdata.2015.55. eCollection 2015.

A multi-source dataset of urban life in the city of Milan and the Province of Trentino

Gianni Barlacchi  1 , Marco De Nadai  2 , Roberto Larcher  3 , Antonio Casella  3 , Cristiana Chitic  3 , Giovanni Torrisi  3 , Fabrizio Antonelli  3 , Alessandro Vespignani  4 , Alex Pentland  5 , Bruno Lepri  6
Affiliations

A multi-source dataset of urban life in the city of Milan and the Province of Trentino

Gianni Barlacchi et al. Sci Data. .

Abstract

The study of socio-technical systems has been revolutionized by the unprecedented amount of digital records that are constantly being produced by human activities such as accessing Internet services, using mobile devices, and consuming energy and knowledge. In this paper, we describe the richest open multi-source dataset ever released on two geographical areas. The dataset is composed of telecommunications, weather, news, social networks and electricity data from the city of Milan and the Province of Trentino. The unique multi-source composition of the dataset makes it an ideal testbed for methodologies and approaches aimed at tackling a wide range of problems including energy consumption, mobility planning, tourist and migrant flows, urban structures and interactions, event detection, urban well-being and many others.

Keywords: Complex networks; Computational science; Geography; Sociology.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Hexbin map with logaritmic color scale of the Province of Trentino.
Each layer represents a specific dataset. In the energy layer the red color represents the sum of consumed electricity. In the precipitation layer colors go from blue (minimum mean intensity of precipitations) to red (the maximum one). In the other layers the blue color represents the minimum number of events (e.g., connections, tweets, news), while the red the maximum number of events. The News pulse map is generated from the News dataset, which is only available for Trento while the Social Pulse map shows the high concentration of Tweets in the biggest cities of Trentino.
Figure 2
Figure 2. The various grid systems employed in this project.
Figure 3
Figure 3. An example of coverage map of Milan.
Figure 4
Figure 4. The SET customers are spatially aggregated into the grid squares and the energy consumption is uniformly divided among the customers, hiding their different type (e.g., houses, condominiums, business activities, industries).
Figure 5
Figure 5. Weekly Z-scaled behavior of SMS, calls, Tweets and Internet CDRs in Milan.
Figure 6
Figure 6. Box-plots showing the calls, SMS, and Internet CDRs distributions per weekday and per cell in Milan.
Figure 7
Figure 7. Weekly spatial behaviour of the six selected areas in Milan and Trentino.
See this image and copyright information in PMC

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References

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