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HARNESSING MOBILITY DATA IN CITIES: A CASE STUDY FROM THE BERGEN REGION

Authors: Ahlers, Dirk; Akerkar, Rajendra; Krogstie, John; Opdahl, Andreas L; Tessem, Bjørnar; Weiqing Zhang;

HARNESSING MOBILITY DATA IN CITIES: A CASE STUDY FROM THE BERGEN REGION

Abstract

Smart cities attempt to use big data, machine learning, and other topical information and communication techniques (ICTs) to improve energy-consumption, mobility, waste management, and other crucial city functions. Many international research projects have been reported but, so far, few of them have addressed mobility in Norwegian cities specifically. This paper reports on a pre-study that focusses on mobility-related data sources in the Bergen region and discusses the needs and opportunities they present. We have identified central actors and the data they own, discussed opportunities and challenges with central stakeholders, developed a taxonomy of data types, and reviewed available ontologies for data integration. We are currently exploring a big-data architecture for harvesting, integrating, and making open mobility data more ready for use through a single-entry point.

Paper presented at NOKOBIT 2018. Published by Bibsys Open Journal Systems.

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Norway
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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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