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Vast amounts of data are collected by service providers and system administ- tors, and are available in public information systems. Data mining technologies provide an ideal framework to assist in analyzing such collections for computer security and surveillance-related endeavors. For instance, system administrators can apply data mining to summarize activity patterns in access logs so that potential malicious incidents can be further investigated. Beyond computer - curity, data mining technology supports intelligence gathering and summari- tion for homeland security. For years, and most recently fueled by events such as September 11, 2001, government agencies have focused on developing and applying data mining technologies to monitor terrorist behaviors in public and private data collections. Theapplicationof data mining to person-speci?cdata raisesseriousconcerns regarding data con?dentiality and citizens' privacy rights. These concerns have led to the adoption of various legislation and policy controls. In 2005, the - ropean Union passed a data-retention directive that requires all telephone and Internetservice providersto store data ontheir consumers for up to two yearsto assist in the prevention of terrorismand organized crime. Similar data-retention regulationproposalsareunderheateddebateintheUnitedStatesCongress. Yet, the debate often focuses on ethical or policy aspects of the problem, such that resolutions have polarized consequences; e. g. , an organization can either share data for data mining purposes or it can not. Fortunately, computer scientists, and data mining researchers in particular, have recognized that technology can beconstructedtosupportlesspolarizedsolutions. Computerscientistsaredev- oping technologies that enable data mining goals without sacri?cing the privacy and security of the individuals to whom the data correspond.

Computer architecture. Operating systems --- Information systems --- Computer. Automation --- ICT (informatie- en communicatietechnieken) --- informatica --- maatschappij --- informatiesystemen --- database management --- informatica management --- computercriminaliteit --- computernetwerken

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Spatial data is essential in a wide range of application domains today. While geographical applications remain the key target area, spatial properties are required in other contexts such as computer-aided design, robotics and image processing. Associated with these is the constantly growing number of distributed processing architectures, based on, for example, grid systems, sensor data networks, and personalized smart devices. Spatial Data on the Web links these two research streams, focusing on the modeling and management of spatial data in distributed systems. Belussi and his coeditors have structured the contributions from internationally renowned researchers into four parts. Part I presents models for representing semistructured, multiresolution and multiscale data; Part II deals with the integration of spatial data sources; Part III describes approaches to spatial data protection; and, finally, Part IV reports innovative applications for mobile devices. The book offers researchers in academia and industry an excellent overview of the state of the art in modeling and management of spatial data in distributed environments, while it may also be the basis of specialized courses on Web-based geographical information systems.

Geodesy. Cartography --- Geology. Earth sciences --- Information systems --- Computer. Automation --- geodesie --- IR (information retrieval) --- informatica --- database management --- geologie