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Conference Paper: A master data management solution to unlock the value of big infrastructure data for smart, sustainable and resilient city planning

TitleA master data management solution to unlock the value of big infrastructure data for smart, sustainable and resilient city planning
Authors
KeywordsBig data
integrated infrastructure asset management
master data management
smart city
smart infrastructure
Issue Date2017
PublisherElsevier: Creative Commons Attribution Non-Commercial No-Derivatives License. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/719240/description#description
Citation
Creative Construction Conference 2017, Primošten, Croatia, 19-22 June 2017. In Procedia Engineering, 2017, v. 196, p. 939-947 How to Cite?
AbstractIn recent years, many governments have launched various smart city or smart infrastructure initiatives to improve the quality of citizens’ life and help city managers / planners optimize the operation and management of urban infrastructures. By deploying internet of things (IoT) to infrastructure systems, high-volume and high-variety of data pertinent to the condition and performance of infrastructure systems along with the behaviors of citizens can be gathered, processed, integrated and analyzed through cloud-based infrastructure asset management systems, ubiquitous mobile applications and big data analytics platforms. Nonetheless, how to fully exploit the value of ‘big infrastructure data’ is still a key challenge facing most stakeholders. Unless data is shared by different infrastructure systems in an interoperable and consistent manner, it is difficult to realize the smart infrastructure concept for efficient smart city planning, not to mention about developing appropriate resilience and sustainable programs. To unlock the value of big infrastructure data for smart, sustainable and resilient city planning, a master data management (MDM) solution is proposed in this paper. MDM has been adopted in the business sector to orchestrate operational and analytical big data applications. In order to derive a suitable MDM solution for smart, sustainable and resilient city planning, commercial and open source MDM systems, smart city standards, smart city concept models, smart community infrastructure frameworks, semantic web technologies will be critically reviewed, and feedback and requirements will be gathered from experts who are responsible for developing smart, sustainable and resilient city programs. A case study which focuses on the building and transportation infrastructures of a selected community in Hong Kong will be conducted to pilot the proposed MDM solution.
Persistent Identifierhttp://hdl.handle.net/10722/245796
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorNg, TST-
dc.contributor.authorXu, J-
dc.contributor.authorYang, Y-
dc.contributor.authorLu, M-
dc.date.accessioned2017-09-18T02:17:03Z-
dc.date.available2017-09-18T02:17:03Z-
dc.date.issued2017-
dc.identifier.citationCreative Construction Conference 2017, Primošten, Croatia, 19-22 June 2017. In Procedia Engineering, 2017, v. 196, p. 939-947-
dc.identifier.issn1877-7058-
dc.identifier.urihttp://hdl.handle.net/10722/245796-
dc.description.abstractIn recent years, many governments have launched various smart city or smart infrastructure initiatives to improve the quality of citizens’ life and help city managers / planners optimize the operation and management of urban infrastructures. By deploying internet of things (IoT) to infrastructure systems, high-volume and high-variety of data pertinent to the condition and performance of infrastructure systems along with the behaviors of citizens can be gathered, processed, integrated and analyzed through cloud-based infrastructure asset management systems, ubiquitous mobile applications and big data analytics platforms. Nonetheless, how to fully exploit the value of ‘big infrastructure data’ is still a key challenge facing most stakeholders. Unless data is shared by different infrastructure systems in an interoperable and consistent manner, it is difficult to realize the smart infrastructure concept for efficient smart city planning, not to mention about developing appropriate resilience and sustainable programs. To unlock the value of big infrastructure data for smart, sustainable and resilient city planning, a master data management (MDM) solution is proposed in this paper. MDM has been adopted in the business sector to orchestrate operational and analytical big data applications. In order to derive a suitable MDM solution for smart, sustainable and resilient city planning, commercial and open source MDM systems, smart city standards, smart city concept models, smart community infrastructure frameworks, semantic web technologies will be critically reviewed, and feedback and requirements will be gathered from experts who are responsible for developing smart, sustainable and resilient city programs. A case study which focuses on the building and transportation infrastructures of a selected community in Hong Kong will be conducted to pilot the proposed MDM solution.-
dc.languageeng-
dc.publisherElsevier: Creative Commons Attribution Non-Commercial No-Derivatives License. The Journal's web site is located at http://www.elsevier.com/wps/find/journaldescription.cws_home/719240/description#description-
dc.relation.ispartofProcedia Engineering-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBig data-
dc.subjectintegrated infrastructure asset management-
dc.subjectmaster data management-
dc.subjectsmart city-
dc.subjectsmart infrastructure-
dc.titleA master data management solution to unlock the value of big infrastructure data for smart, sustainable and resilient city planning-
dc.typeConference_Paper-
dc.identifier.emailNg, TST: tstng@hku.hk-
dc.identifier.emailXu, J: frankxu@hkucc.hku.hk-
dc.identifier.emailLu, M: lumx@hku.hk-
dc.identifier.authorityNg, TST=rp00158-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1016/j.proeng.2017.08.034-
dc.identifier.hkuros278103-
dc.identifier.hkuros290297-
dc.identifier.volume196-
dc.identifier.spage939-
dc.identifier.epage947-
dc.identifier.isiWOS:000418465300122-
dc.publisher.placeNetherlands-

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