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Big Data Analytics and Smart Cities: A Loose or Tight Couple?
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-4250-4752
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-4317-9963
2017 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Smart City (SC) is an emerging concept aiming at mitigating the challenges raised due to the continuous urbanization development. To face these challenges, government decision makers sponsor SC projects targeting sustainable economic growth and better quality of life for inhabitants and visitors. Information and Communication Technologies (ICT) is the enabling technology for smartening. These technologies yield massive volumes of data known as Big Data (BD). If spawned BD are integrated and analyzed, both city decision makers and citizens can benefit from valuable insights and information services. The process of extracting information and insights from BD is known as Big Data Analytics (BDA). Although BDA involves non-trivial challenges, it attracted academician and industrialist. Surveying the literature reveals the novelty and increasing interest in addressing BD applications in SCs. Although literature is replete with abundant number of articles about SCs applications harnessing BD, comprehensive discussion on BDA frameworks fitting SCs requirements is still needed. This paper attempts to fill this gap. It is a systematic literature review on BDA frameworks in SCs. In this review, we will try to answer the following research questions: what are the big data analytics frameworks applied in smart cities? what are the functional gaps in the current available frameworks? what are the conceptual guidelines of designing integrated scalable big data analytics frameworks for smart cities purposes? The paper concludes with a proposal for a novel conceptual analytics framework to serve SCs requirements. Additionally, open issues and further research directions are presented.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Big data, Big data analytics Frameworks, Smart cities
National Category
Computer Science Information Systems, Social aspects
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-63718OAI: oai:DiVA.org:ltu-63718DiVA: diva2:1105669
Conference
International Conference on Connected Smart Cities 2017 (CSC 2017), Lisbon, 20-22 July 2017
Available from: 2017-06-05 Created: 2017-06-05 Last updated: 2017-06-29Bibliographically approved

Open Access in DiVA

fulltext(477 kB)109 downloads
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Osman, Ahmed M. ShahatElragal, AhmedBergvall-Kåreborn, Birgitta
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