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Data volumes have increased so significantly that the authors need to carefully consider how they interact with, share, and analyze data to avoid bottlenecks. In contexts such as e-Science and scientific computing, a large emphasis is placed on collaboration, resulting in many well-known challenges in ensuring that data is in the right place at the right time and accessible by the right users. Yet these simple requirements create substantial challenges for the distribution, analysis, storage, and replication of potentially "Large" datasets. Additional complexity is added through constraints such as budget, data locality, usage, and available local storage.
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