Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/59997

Data in the Wild: A KM Approach to Doing a Census Without Asking Anyone and the Issue of Privacy

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dc.contributor.author Kelly, James
dc.contributor.author Jennex, Murray
dc.contributor.author Abhari, Kaveh
dc.contributor.author Durcikova, Alexandra
dc.contributor.author Frost, Eric
dc.date.accessioned 2019-01-03T00:40:05Z
dc.date.available 2019-01-03T00:40:05Z
dc.date.issued 2019-01-08
dc.identifier.isbn 978-0-9981331-2-6
dc.identifier.uri http://hdl.handle.net/10125/59997
dc.description.abstract Knowledge Societies strive to better their citizens by maximizing services while minimizing costs. One of the more expensive activities is conducting a census. This paper explores the feasibility of conducting a smart census by using a knowledge management strategy of focusing on actionable intelligence and the use of open source data sources to conduct a national census. Both technical and data privacy feasibility is discussed.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Knowledge Management and Information Security
dc.subject Knowledge Innovation and Entrepreneurial Systems
dc.subject Actionable Intelligence, Knowledge Management Strategy, Open Source Data, Privacy
dc.title Data in the Wild: A KM Approach to Doing a Census Without Asking Anyone and the Issue of Privacy
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2019.675
Appears in Collections: Knowledge Management and Information Security


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