Data analysis, modeling, and visualization in smart cities

Carlos Carrasco-Farré; Ignasi Alcalde; Didier Grimaldi

doi:10.1016/B978-0-12-821122-9.00010-5

Data analysis, modeling, and visualization in smart cities

Carlos Carrasco-Farré
, Ignasi Alcalde
, Didier Grimaldi

La Salle Digital Engineering School

Research output: Book chapter › Chapter › peer-review

1 Citation (Scopus)

Abstract

The rise of data is a fact, and its volume is estimated to double every 1.2years. After data is collected, processed, and modeled, the relationships need to be visualized so a conclusion can be made. Cities have two things in abundance: data and unanswered questions. Sometimes, the challenge is not so much about generating and capturing more data but rather discovering new ways to condense, interpret, and make decisions regarding this data. And for that the key lies in data visualization, which is one of the best-known methods to reduce and illustrate data in a simplified and visual way.

Original language	English
Title of host publication	Implementing Data-Driven Strategies in Smart Cities
Subtitle of host publication	A Roadmap for Urban Transformation
Publisher	Elsevier
Pages	173-195
Number of pages	23
ISBN (Electronic)	9780128211229
ISBN (Print)	9780128211236
DOIs	https://doi.org/10.1016/B978-0-12-821122-9.00010-5
Publication status	Published - 1 Jan 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Analyzing data
Dashboard
Data visualization
Infographics
Key performance indicators

Access to Document

10.1016/B978-0-12-821122-9.00010-5

Cite this

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AU - Grimaldi, Didier

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KW - Data visualization

KW - Infographics

KW - Key performance indicators

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M3 - Chapter

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BT - Implementing Data-Driven Strategies in Smart Cities

PB - Elsevier

ER -

Data analysis, modeling, and visualization in smart cities

Abstract

UN SDGs

Keywords

Access to Document

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