2016 New York Scientific Data Summit (NYSDS) 2016
DOI: 10.1109/nysds.2016.7747811
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Data storage and sharing for the long tail of science

Abstract: Research data infrastructure such as storage must now accommodate new requirements resulting from trends in research data management that require researchers to store their data for the long term and make it available to other researchers. We propose Data Depot, a system and service that provides capabilities for shared space within a group, shared applications, flexible access patterns and ease of transfer at Purdue University. We evaluate Depot as a solution for storing and sharing multiterabytes of data pro… Show more

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Cited by 4 publications
(2 citation statements)
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“…Requirements for reproducibility are numerous and unclear and only started to be explored in details every step of a computational experiment (Carpen-Amarie et al, 2014). Recent recommendations include publishing source code, computational environments, and workflows in trusted repositories with persistent identifiers and links (Zhang et al, 2016a), as well as designing incentives to encourage reproducibility by journals and funding agencies (Stodden et al, 2016).…”
Section: Related Workmentioning
confidence: 99%
“…Requirements for reproducibility are numerous and unclear and only started to be explored in details every step of a computational experiment (Carpen-Amarie et al, 2014). Recent recommendations include publishing source code, computational environments, and workflows in trusted repositories with persistent identifiers and links (Zhang et al, 2016a), as well as designing incentives to encourage reproducibility by journals and funding agencies (Stodden et al, 2016).…”
Section: Related Workmentioning
confidence: 99%
“…Part of the challenge is the long tail of data, where different communities, small research teams and individual experiments have specific requirements on how the data is stored and catalogued [16]. Each community or individual scientist working on small projects produce a large portion of the total scientific output and do not have many resources to make the data accessible to the wider public [35]. With funding agencies requiring data management plans upfront [13,25], storing data on local hard drives is not feasible anymore.…”
Section: Introductionmentioning
confidence: 99%