An Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development

Handle URI:
http://hdl.handle.net/10754/552353
Title:
An Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development
Authors:
Douglas, Craig C.
Abstract:
In 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.
KAUST Department:
Numerical Porous Media SRI Center (NumPor); SRI Uncertainty Quantification Center
Citation:
An Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development 2014, 29:1246 Procedia Computer Science
Journal:
Procedia Computer Science
Conference/Event name:
14th Annual International Conference on Computational Science, ICCS 2014
Issue Date:
6-Jun-2014
DOI:
10.1016/j.procs.2014.05.112
Type:
Conference Paper
ISSN:
18770509
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S1877050914002890
Appears in Collections:
Conference Papers

Full metadata record

DC FieldValue Language
dc.contributor.authorDouglas, Craig C.en
dc.date.accessioned2015-05-06T13:18:25Zen
dc.date.available2015-05-06T13:18:25Zen
dc.date.issued2014-06-06en
dc.identifier.citationAn Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Development 2014, 29:1246 Procedia Computer Scienceen
dc.identifier.issn18770509en
dc.identifier.doi10.1016/j.procs.2014.05.112en
dc.identifier.urihttp://hdl.handle.net/10754/552353en
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.en
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1877050914002890en
dc.rightsArchived with thanks to Procedia Computer Science. http://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectBig dataen
dc.subjectDDDASen
dc.subjectdynamic data driven applicationsen
dc.subjectopen source softwareen
dc.subjectsensor networksen
dc.subjectuncertainty quantificationen
dc.subjectanomaly detectionen
dc.titleAn Open Framework for Dynamic Big-data-driven Application Systems (DBDDAS) Developmenten
dc.typeConference Paperen
dc.contributor.departmentNumerical Porous Media SRI Center (NumPor)en
dc.contributor.departmentSRI Uncertainty Quantification Centeren
dc.identifier.journalProcedia Computer Scienceen
dc.conference.date2014-06-10 to 2014-06-12en
dc.conference.name14th Annual International Conference on Computational Science, ICCS 2014en
dc.conference.locationCairns, QLD, AUSen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUniversity of Wyoming, School of Energy Resources, Laramie, WY, U.S.Aen
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