V for variety: lessons learned from complex smart cities data harmonization and integration

Iman Avazpour, John Grundy, Liming Zhu

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

2 Citations (Scopus)

Abstract

With emerging trends for Internet of Things (IoT) and Smart Cities, complex data transformation, aggregation and visualization problems are becoming increasingly common. These tasks support improved business intelligence, analytics and enduser access to data. However, in most cases developers of these tasks are presented with challenging problems including noisy data, diverse data formats, data modeling and increasing demand for sophisticated visualization support. This paper describes our experiences with just such problems in the context of Household Travel Surveys data integration and harmonization. We describe a common approach for addressing these harmonizations. We then discuss a set of lessons that we have learned from our experience that we hope will be useful for others embarking on similar problems. We also identify several key directions and needs for future research and practical support in this area.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016
EditorsChiara Boldrini, Salil Kanhere
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781509019410, 9781509019403
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventIEEE International Workshop on Context-Aware Smart Cities and Intelligent Transport Systems 2016 - Sydney, Australia
Duration: 14 Mar 201618 Mar 2016
Conference number: 1st
http://awarecities.org/

Conference

ConferenceIEEE International Workshop on Context-Aware Smart Cities and Intelligent Transport Systems 2016
Abbreviated titleAwareCities2016
Country/TerritoryAustralia
CitySydney
Period14/03/1618/03/16
Internet address

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