| Transactions on Large-Scale Data- And Knowledge-Centered Systems IV: Special Issue on Database Systems for Biomedical Applications Contributor(s): Hameurlain, Abdelkader (Editor in Chief), Küng, Josef (Editor in Chief), Wagner, Roland (Editor in Chief) |
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ISBN: 3642237398 ISBN-13: 9783642237393 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback - Other Formats Published: October 2011 |
| Additional Information |
| BISAC Categories: - Computers | Databases - Data Mining - Computers | System Administration - Storage & Retrieval - Computers | Information Technology |
| Dewey: 005.74 |
| Series: Lecture Notes in Computer Science: Journal Subline |
| Physical Information: 0.7" H x 6.1" W x 9.2" (0.75 lbs) 209 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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 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. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between Grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This special issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems highlights some of the major challenges emerging from the biomedical applications that are currently inspiring and promoting database research. These include the management, organization, and integration of massive amounts of heterogeneous data; the semantic gap between high-level research questions and low-level data; and privacy and efficiency. The contributions cover a large variety of biological and medical applications, including genome-wide association studies, epidemic research, and neuroscience. |