Extracting Insights: A Data Centre Architecture Approach in Million Genome Era -- Dynamic Estimation and Grid Partitioning Approach for Multi-objective Optimization Problems in Medical Cloud Federations -- Temporal Pattern Mining for E-Commerce Dataset -- Scalable Schema Discovery for RDF Data -- Load-Aware Shedding in Stream Processing Systems -- Selectivity Estimation with Attribute Value Dependencies Using Linked Bayesian Networks.

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 46th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains six fully revised selected regular papers. Topics covered include an elastic framework for genomic data management, medical data cloud federations, temporal pattern mining, scalable schema discovery, load shedding, and selectivity estimation using linked Bayesian networks.

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