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


Autoria(s): Avazpour, Iman; Grundy, John; Zhu, Liming
Contribuinte(s)

[Unknown]

Data(s)

01/01/2016

Resumo

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.

Identificador

http://hdl.handle.net/10536/DRO/DU:30083604

Idioma(s)

eng

Publicador

IEEE

Relação

http://dro.deakin.edu.au/eserv/DU:30083604/avazpour-vforvariety-2016.pdf

http://dro.deakin.edu.au/eserv/DU:30083604/avazpour-vforvariety-evid-2016.pdf

http://www.dx.doi.org/10.1109/PERCOMW.2016.7457092

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7452853

Direitos

2016, IEEE

Palavras-Chave #data models #data integration #smart cities
Tipo

Conference Paper