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On-Demand Big Data Analysis in Digital Repositories

dc.contributor.authorXie, Zhiwuen
dc.contributor.authorChen, Yinlinen
dc.contributor.authorJiang, Tingtingen
dc.contributor.authorGriffin, Julieen
dc.contributor.authorWalters, Tyleren
dc.contributor.authorTarazaga, Pablo Albertoen
dc.contributor.authorKasarda, Mary E.en
dc.date.accessioned2016-06-26T15:22:24Zen
dc.date.available2016-06-26T15:22:24Zen
dc.date.issued2015-12-18en
dc.description.abstractWe describe a use and reuse driven digital repository integrated with lightweight data analysis capabilities provided by the Docker framework. Using building sensor data collected from the Virginia Tech Goodwin Hall Living La- boratory, we perform evaluations using Amazon EC2 and Container Service with a Fedora 4 repository backed with storage in Amazon S3. The results con- firm the viability and benefits of this approach.en
dc.identifier.doihttps://doi.org/10.1007/978-3-319-27974-9_29en
dc.identifier.isbn978-3-319-27973-2en
dc.identifier.issn0302-9743en
dc.identifier.urihttp://hdl.handle.net/10919/71473en
dc.identifier.volume9469en
dc.language.isoen_USen
dc.publisherSpringer International Publishingen
dc.relation.ispartof17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Seoul, Korea, December 9-12, 2015en
dc.relation.ispartofseriesLecture Notes in Computer Science;en
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 United Statesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/en
dc.subjectBig dataen
dc.subjectData managementen
dc.subjectDockeren
dc.subjectScholarly digital divideen
dc.subjectUse and reuse driven approachen
dc.titleOn-Demand Big Data Analysis in Digital Repositoriesen
dc.title.serialDigital Libraries: Providing Quality Informationen
dc.typeBook chapteren

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