An ontological approach to dynamic fine-grained Urban Indicators

Pileggi, SF; Hunter, J

An ontological approach to dynamic fine-grained Urban Indicators

Pileggi, SF

Hunter, J

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Publication Type:: Journal Article
Citation:: Procedia Computer Science, 2017, 108 pp. 2059 - 2068
Issue Date:: 2017-01-01

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Field	Value	Language
dc.contributor.author	Pileggi, SF https://orcid.org/0000-0001-9722-2205	en_US
dc.contributor.author	Hunter, J	en_US
dc.date.issued	2017-01-01	en_US
dc.identifier.citation	Procedia Computer Science, 2017, 108 pp. 2059 - 2068	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126453
dc.description.abstract	© 2017 The Authors. Published by Elsevier B.V. Urban indicators provide a unique multi-disciplinary data framework which social scientists, planners and policy makers employ to understand and analyze the complex dynamics of metropolitan regions. Indicators provide an independent, quantitative measure or benchmark of an aspect of an urban environment, by combining different metrics for a given region. While the current approach to urban indicators involves the systematic accurate collection of the raw data required to produce reliable indicators and the standardization of well-known commonly accepted or widely adopted indicators, the next generation of indicators is expected to support a more dynamic, customizable, fine-grained approach to indicators, via a context of interoperability and linked open data. Within this paper, we address these emerging requirements through an ontological approach aimed at (i) establishing interoperability among heterogeneous data sets, (ii) expressing the high-level semantics of the indicators, (iii) supporting indicator adaptability and dynamic composition for specific applications and (iv) representing properly the uncertainties of the resulting ecosystem.	en_US
dc.relation.ispartof	Procedia Computer Science	en_US
dc.relation.isbasedon	10.1016/j.procs.2017.05.003	en_US
dc.title	An ontological approach to dynamic fine-grained Urban Indicators	en_US
dc.type	Journal Article
utslib.citation.volume	108	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	1005 Communications Technologies	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - PERSWADE - Centre on Persuasive Systems for Wise Adaptive Living
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	108	en_US

Abstract:

© 2017 The Authors. Published by Elsevier B.V. Urban indicators provide a unique multi-disciplinary data framework which social scientists, planners and policy makers employ to understand and analyze the complex dynamics of metropolitan regions. Indicators provide an independent, quantitative measure or benchmark of an aspect of an urban environment, by combining different metrics for a given region. While the current approach to urban indicators involves the systematic accurate collection of the raw data required to produce reliable indicators and the standardization of well-known commonly accepted or widely adopted indicators, the next generation of indicators is expected to support a more dynamic, customizable, fine-grained approach to indicators, via a context of interoperability and linked open data. Within this paper, we address these emerging requirements through an ontological approach aimed at (i) establishing interoperability among heterogeneous data sets, (ii) expressing the high-level semantics of the indicators, (iii) supporting indicator adaptability and dynamic composition for specific applications and (iv) representing properly the uncertainties of the resulting ecosystem.

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http://hdl.handle.net/10453/126453