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Using Active Data to Provide Smart Data Surveillance to E-Science Users
2015
2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing
Modern scientific experiments often involve multiple storage and computing platforms, software tools, and analysis scripts. The resulting heterogeneous environments make data management operations challenging; the significant number of events and the absence of data integration makes it difficult to track data provenance, manage sophisticated analysis processes, and recover from unexpected situations. Current approaches often require costly human intervention and are inherently error prone. The
doi:10.1109/pdp.2015.76
dblp:conf/pdp/SimonetCFF15
fatcat:7rkvxivepbhobdrqlovsgacwna