Mining Urban Data (Part B)

Gennady Andrienko; Dimitrios Gunopulos; Yannis Ioannidis; Vana Kalogeraki; Ioannis Katakis; Katharina Morik; Olivier Verscheure

doi:10.1016/j.is.2016.01.001

Mining Urban Data (Part B)

Gennady Andrienko, Dimitrios Gunopulos, Yannis Ioannidis, Vana Kalogeraki, Ioannis Katakis, Katharina Morik, Olivier Verscheure

Department of Computer Science

Research output: Contribution to journal › Review article › peer-review

Abstract

Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens' quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic 'Mining Urban Data' published in the journal Information Systems.

Original language	English
Pages (from-to)	75-76
Number of pages	2
Journal	Information Systems
Volume	57
DOIs	https://doi.org/10.1016/j.is.2016.01.001
Publication status	Published - 1 Apr 2016

Keywords

Data management
Data mining
Sensor networks
Smart cities
Social networks
Urban data

UN SDGs

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

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10.1016/j.is.2016.01.001

Cite this

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title = "Mining Urban Data (Part B)",

abstract = "Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens' quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic 'Mining Urban Data' published in the journal Information Systems.",

keywords = "Data management, Data mining, Sensor networks, Smart cities, Social networks, Urban data",

author = "Gennady Andrienko and Dimitrios Gunopulos and Yannis Ioannidis and Vana Kalogeraki and Ioannis Katakis and Katharina Morik and Olivier Verscheure",

year = "2016",

month = apr,

day = "1",

doi = "10.1016/j.is.2016.01.001",

language = "English",

volume = "57",

pages = "75--76",

journal = "Information Systems",

issn = "0306-4379",

publisher = "Wiley-Blackwell Publishing Ltd",

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TY - JOUR

T1 - Mining Urban Data (Part B)

AU - Andrienko, Gennady

AU - Gunopulos, Dimitrios

AU - Ioannidis, Yannis

AU - Kalogeraki, Vana

AU - Katakis, Ioannis

AU - Morik, Katharina

AU - Verscheure, Olivier

PY - 2016/4/1

Y1 - 2016/4/1

N2 - Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens' quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic 'Mining Urban Data' published in the journal Information Systems.

AB - Modern cities are flooded with data. New information sources like public transport and wearable devices provide opportunities for novel applications that will improve citizens' quality of life. From a data science perspective, data emerging from smart cities give rise to a lot of challenges that constitute a new interdisciplinary field of research. This article introduces the second part of a special issue on the topic 'Mining Urban Data' published in the journal Information Systems.

KW - Data management

KW - Data mining

KW - Sensor networks

KW - Smart cities

KW - Social networks

KW - Urban data

UR - https://www.scopus.com/pages/publications/84957837547

U2 - 10.1016/j.is.2016.01.001

DO - 10.1016/j.is.2016.01.001

M3 - Review article

AN - SCOPUS:84957837547

SN - 0306-4379

VL - 57

SP - 75

EP - 76

JO - Information Systems

JF - Information Systems

ER -

Mining Urban Data (Part B)

Abstract

Keywords

UN SDGs

Access to Document

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