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Scalable analytics over unstructured multidimensional time-series data

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dc.contributor.authorPallickara, Sangmi Lee, author
dc.contributor.authorColorado State University, publisher
dc.date.accessioned2015-09-04T14:29:41Z
dc.date.available2015-09-04T14:29:41Z
dc.date.issued2015-05-07
dc.descriptionPresented at the National data integrity conference: enabling research: new challenges & opportunities held on May 7-8, 2015 at Colorado State University, Fort Collins, Colorado. Researchers, administrators and integrity officers are encountering new challenges regarding research data and integrity. This conference aims to provide attendees with both a high level understanding of these challenges and impart practical tools and skills to deal with them. Topics will include data reproducibility, validity, privacy, security, visualization, reuse, access, preservation, rights and management.
dc.descriptionPowerPoint presentation given on May 7, 2015.
dc.format.mediumborn digital
dc.format.mediumPresentation slides
dc.identifier.urihttp://hdl.handle.net/10217/167268
dc.identifier.urihttp://dx.doi.org/10.25675/10217/167268
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof1st Annual National Data Integrity Conference (2015)
dc.relation.ispartofNational data integrity conference, 2015
dc.rights.licenseThis presentation is open access and distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectlarge scale data analysis
dc.subjectdistributed storage
dc.subjectGalileo
dc.titleScalable analytics over unstructured multidimensional time-series data
dc.typeText

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1st Annual National Data Integrity Conference, 2015