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dc.contributor.authorul Hassan, Umair
dc.contributor.authorHasan, Souleiman
dc.contributor.authorDerguech, Wassim
dc.contributor.authorHannon, Louise
dc.contributor.authorClifford, Eoghan
dc.contributor.authorKouroupertroglou, Christos
dc.contributor.authorSmit, Sander
dc.contributor.authorCurry, Edward
dc.date.accessioned2019-03-27T14:58:26Z
dc.date.available2019-03-27T14:58:26Z
dc.date.issued2017
dc.identifier.citationul Hassan, Umair, Hasan, Souleiman, Derguech, Wassim, Hannon, Louise, Clifford, Eoghan, Kouroupertroglou, Christos, Smit, Sander, Curry, Edward. (2017). Water analytics and management with real-time linked dataspaces. In Adegboyega Ojo & Jeremy Millard (Eds.), Government 3.0 – Next Generation Government Technology Infrastructure and Services. New York City : Springer.en_IE
dc.identifier.isbn978-3-319-63743-3
dc.identifier.urihttp://hdl.handle.net/10379/15062
dc.description.abstractDue to predictions of water scarcity in the future, governments and public administrations are increasingly looking for innovative solutions to improve water governance and conservation. The problem is exasperated due to low levels of awareness about water consumption among the general public. This calls for a holistic approach to effectively manage resources during all stages of water usage. Implementation of such an approach heavily relies on advanced analytics technologies that combine data from different sources to enable decision support and public engagement. The next-generation of water information management systems must overcome significant technical challenges including integration of heterogeneous and real-time data, creation of analytical models for diverse users, and exploitation of ubiquitous devices to disseminate actionable information. This chapter presents a new approach for water analytics in public spaces that is built upon the fundamental concepts of Linked Data technologies. The chapter also presents a concrete realization of the Linked Data approach through the development of water analytics applications for buildings in public educational institutions.en_IE
dc.description.sponsorshipThe research leading to these results has received funding under the European Commission’s Seventh Framework Programme from ICT grant agreement WATERNOMICS no. 619660. It is supported in part by Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289.en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSpringeren_IE
dc.relation.ispartofGovernment 3.0 - Next Generation Government Technology Infrastructure and Servicesen
dc.subjectWater analyticsen_IE
dc.subjectLinked dataspacesen_IE
dc.titleWater analytics and management with real-time linked dataspacesen_IE
dc.typeBook chapteren_IE
dc.date.updated2019-03-22T16:41:10Z
dc.identifier.doi10.1007/978-3-319-63743-3
dc.local.publishedsourcehttps://dx.doi.org/10.1007/978-3-319-63743-3en_IE
dc.description.peer-reviewedPeer reviewed
dc.contributor.funderSeventh Framework Programmeen_IE
dc.contributor.funderScience Foundation Irelanden_IE
dc.internal.rssid12751141
dc.local.contactEoghan Clifford, Room 1035, Alice Perry Engineering Building, Nui Galway, Galway. 2219 Email: eoghan.clifford@nuigalway.ie
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
dcterms.projectinfo:eu-repo/grantAgreement/EC/FP7::SP1::ICT/619660/EU/ICT for Water Resource Management/WATERNOMICSen_IE
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
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