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Title	Enabling Smart City Provenance-Based Applications To Improve Urban Mobility In Brazilian Cities
ID_Doc	23045
Authors	Serra da Cruz S.M.; Macário Costa R.J.
Year	2018
Published	Sustainable Transportation and Smart Logistics: Decision-Making Models and Solutions
DOI	http://dx.doi.org/10.1016/B978-0-12-814242-4.00017-X
Abstract	Open Government Data (OGD) combined with mobile data collected from citizens' smartphones have the potential for innovative urban services to enable smart cities. However, one of the main challenges for the consolidation of smart cities applications in emerging countries is the limited offer of high-quality data and the availability of strategies that increase the interaction and collaboration between government and civil society. Our work aims to offer solutions related to the challenges of sustainable transportation and urban mobility in Brazilian cities. This chapter adopts concepts and methodologies from the emerging field of urban computing. It aims to contribute to the challenges of using OGD enriched with data provenance in mobile applications about public bus transportation. We illustrate our approach with a distributed architecture named BusInRio, which uses standardized interfaces to access curated OGD and implements services to manage the associated metadata. We also present two studies based on users using OGD enriched with retrospective provenance. © 2019 Elsevier Inc. All rights reserved..
Author Keywords	Data provenance; Data quality; Mobile application; Open Government Data; Smart cities; Sustainability; Transportation; Workflows

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