dc.contributor.author | Bibri, Simon Elias | |
dc.contributor.author | Krogstie, John | |
dc.date.accessioned | 2019-03-04T12:41:07Z | |
dc.date.available | 2019-03-04T12:41:07Z | |
dc.date.created | 2019-01-13T18:37:17Z | |
dc.date.issued | 2018 | |
dc.identifier.isbn | 978-1-4503-6562-8 | |
dc.identifier.uri | http://hdl.handle.net/11250/2588493 | |
dc.description.abstract | There has recently been much enthusiasm about the possibilities created by the big data deluge to better understand, monitor, analyze, and plan modern cities to improve their contribution to the goals of sustainable development. Indeed, much of our knowledge of urban sustainability has been gleaned from studies that are characterized by data scarcity. Therefore, this paper endeavors to develop a systematic framework for urban sustainability analytics based on a cross-industry standard process for data mining. The intention is to enable well-informed decision-making and enhanced insights in relation to diverse urban domains. We argue that there is tremendous potential to transform and advance the knowledge of smart sustainable cities through the creation of a big data deluge that seeks to provide much more sophisticated, wider-scale, finer-grained, real-time understanding, and control of various aspects of urbanity in the undoubtedly upcoming Exabyte Age. | nb_NO |
dc.language.iso | eng | nb_NO |
dc.publisher | Association for Computing Machinery (ACM) | nb_NO |
dc.relation.ispartof | SCA '18: Proceedings of the 3rd International Conference on Smart City Applications | |
dc.title | The Big Data Deluge for Transforming the Knowledge of Smart Sustainable Cities: A Data Mining Framework for Urban Analytics | nb_NO |
dc.type | Chapter | nb_NO |
dc.description.version | acceptedVersion | nb_NO |
dc.identifier.doi | 10.1145/3286606.3286788 | |
dc.identifier.cristin | 1655691 | |
dc.description.localcode | © ACM, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions of Computing Education, https://doi.org/10.1145/3286606.3286788 | nb_NO |
cristin.unitcode | 194,63,10,0 | |
cristin.unitname | Institutt for datateknologi og informatikk | |
cristin.ispublished | true | |
cristin.fulltext | postprint | |
cristin.qualitycode | 1 | |