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

Fraunhofer Institute for Intelligent Analysis and Information Systems
City, University of London
National and Kapodistrian University of Athens
Athens University of Economics and Business
TU Dortmund University
IBM Research

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

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Keywords

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

Access to Document

10.1016/j.is.2016.01.001

Cite this

@article{e96016a26faa427b9aa57b2fb7fe47fd,

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",

}

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

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this