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survey

A Systematic Review for Smart City Data Analytics

Published: 04 December 2018 Publication History

Abstract

Smart cities (SCs) are becoming highly sophisticated ecosystems at which innovative solutions and smart services are being deployed. These ecosystems consider SCs as data production and sharing engines, setting new challenges for building effective SC architectures and novel services. The aim of this article is to “connect the pieces” among Data Science and SC domains, with a systematic literature review which identifies the core topics, services, and methods applied in SC data monitoring. The survey focuses on data harvesting and data mining processes over repeated SC data cycles. A survey protocol is followed to reach both quantitative and semantically important entities. The review results generate useful taxonomies for data scientists in the SC context, which offers clear guidelines for corresponding future works. In particular, a taxonomy is proposed for each of the main SC data entities, namely, the “D Taxonomy” for the data production, the “M Taxonomy” for data analytics methods, and the “S Taxonomy” for smart services. Each of these taxonomies clearly places entities in a classification which is beneficial for multiple stakeholders and for multiple domains in urban smartness targeting. Such indicative scenarios are outlined and conclusions are quite promising for systemizing.

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cover image ACM Computing Surveys
ACM Computing Surveys  Volume 51, Issue 5
September 2019
791 pages
ISSN:0360-0300
EISSN:1557-7341
DOI:10.1145/3271482
  • Editor:
  • Sartaj Sahni
Issue’s Table of Contents
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Publication History

Published: 04 December 2018
Accepted: 01 July 2018
Revised: 01 April 2018
Received: 01 December 2017
Published in CSUR Volume 51, Issue 5

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  1. Data mining
  2. Internet of Things
  3. crowd-sensing
  4. crowd-sourcing
  5. data harvesting
  6. open data
  7. smart cities
  8. smart dimensions
  9. smart services
  10. systematic review
  11. taxonomy

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