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dc.contributor.authorDouglas, Craig
dc.date.accessioned2015-05-06T13:18:25Z
dc.date.available2015-05-06T13:18:25Z
dc.date.issued2014-06-06
dc.identifier.citationAn Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development 2014, 29:1246 Procedia Computer Science
dc.identifier.issn18770509
dc.identifier.doi10.1016/j.procs.2014.05.112
dc.identifier.urihttp://hdl.handle.net/10754/552353
dc.description.abstractIn this paper, we outline key features that dynamic data-driven application systems (DDDAS) have. A DDDAS is an application that has data assimilation that can change the models and/or scales of the computation and that the application controls the data collection based on the computational results. The term Big Data (BD) has come into being in recent years that is highly applicable to most DDDAS since most applications use networks of sensors that generate an overwhelming amount of data in the lifespan of the application runs. We describe what a dynamic big-data-driven application system (DBDDAS) toolkit must have in order to provide all of the essential building blocks that are necessary to easily create new DDDAS without re-inventing the building blocks.
dc.publisherElsevier BV
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1877050914002890
dc.rightsArchived with thanks to Procedia Computer Science. http://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectBig data
dc.subjectDDDAS
dc.subjectdynamic data driven applications
dc.subjectopen source software
dc.subjectsensor networks
dc.subjectuncertainty quantification
dc.subjectanomaly detection
dc.titleAn Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentNumerical Porous Media SRI Center (NumPor)
dc.contributor.departmentSRI Uncertainty Quantification Center
dc.identifier.journalProcedia Computer Science
dc.conference.date2014-06-10 to 2014-06-12
dc.conference.name14th Annual International Conference on Computational Science, ICCS 2014
dc.conference.locationCairns, QLD, AUS
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionUniversity of Wyoming, School of Energy Resources, Laramie, WY, U.S.A
kaust.personDouglas, Craig
refterms.dateFOA2018-06-13T16:54:46Z


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