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On-Demand Big Data Analysis in Digital Repositories: A Lightweight Approach

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Digital Libraries: Providing Quality Information (ICADL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9469))

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Abstract

We 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 Laboratory, we perform evaluations using Amazon EC2 and Container Service with a Fedora 4 repository backed with storage in Amazon S3. The results confirm the viability and benefits of this approach.

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Correspondence to Zhiwu Xie .

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Xie, Z. et al. (2015). On-Demand Big Data Analysis in Digital Repositories: A Lightweight Approach. In: Allen, R., Hunter, J., Zeng, M. (eds) Digital Libraries: Providing Quality Information. ICADL 2015. Lecture Notes in Computer Science(), vol 9469. Springer, Cham. https://doi.org/10.1007/978-3-319-27974-9_29

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  • DOI: https://doi.org/10.1007/978-3-319-27974-9_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27973-2

  • Online ISBN: 978-3-319-27974-9

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