Kevin Shaw – författare

Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites. Today, businesses are either migrating location-specific capabilities into their information systems, or expanding existing Geospatial Information Systems (GIS) implementation into enterprise-wide solutions. As enterprise information systems evolve toward service-oriented architecture (SOA), geospatial technologies also evolve along the same lines.Geospatial Services and Applications for the Internet covers a wide spectrum of techniques, algorithms and modeling methodologies that address the challenges in service-oriented architectural design for GIS, and intelligent processing for spatial queries. This book presents in-depth studies on performance improvement, data integration, service personalization and interoperation between geospatial services. These studies provide the reader with a wide spectrum of examples and case studies on the development of GIS for hydrological applications, electrical power supply applications, land usage and urban planning, and NASA’s Earth image datasets dissemination.Geospatial Services and Applications for the Internet is designed for a professional audience composed of practitioners and researchers in industry.  This book is also suitable as a secondary text book or reference for advanced-level students in computer science and geosciences.

Stately and majestic, yet scuffed with wear and disillusion, the poems of Smaller Hours mount the sky like columns and fora of some archaic ruin. Through these ancient halls, Kevin Shaw tracks Eros, clearing away the rubble and polishing the marble, along the way exploring queer ways of keeping time. Music and movies, clocks and inventors populate these poems. History casts a shadow over all.Kevin Shaw's debut collection is a tour de force of control and grace; musical lines anchored by powerful rhythms dance into the reader's ear. The speakers of these lyrics encounter Nijinsky in a waiting room, Ovid at the laundromat, or re-enact a devastating flood after a night of drinking. From a mixtape full of quarter-century-old regrets, to the sensuality of a harmonica buzzing against pursed lips, to the violence and hope of Stonewall, Smaller Hours collapses the past with the present and the personal with the public, taking a sideways glance at historical figures — inventors, poets, movie stars — from across a gay bar's crowded dance floor.

We are facing a rapidly growing capability to collect more and more data regarding our environment. With that, we must have the ability to extract more insightful knowledge about the environmental processes at work on the earth. Spatio-temporal information systems (STIS) should prove beneficial in producing useful knowledge about changes in our world from these ever-burgeoning collections of environment data. STIS provide the ability to store, analyze and represent the dynamic properties of the environment, that is, geographic information in space and time. A STIS, for example, can produce a weather map, but more importantly, it can present a user with information in map or report form indicating how precipitation progresses in space over time to affect a watershed. Other uses include forestry and even electrical systems management. Forestry experts using an STIS are able to examine the rates of movements of forest fires, how they evolve over time, and their impact on forest growth over long periods of time. A large electrical network system manager uses an STIS to track the failures and repairs of electrical transformers.Use of an STIS in this case allows the reconstruction of the status of the network at any given past time. This title is an edited volume is composed of chapters from experts in the field and addresses the many issues in support of modelling, creation, querying, visualizing and mining. The book is intended to bring together a coherent body of knowledge relating to STIS data modelling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the most up-to-date techniques for the practical design of STIS, essential for complex query processing. It is structured to meet the needs of practitioners and researchers in industry and graduate-level students in computer science.

Researchers in data management have recently recognized the importance of a new class of data-intensive applications that requires managing data streams, i.e., data composed of continuous, real-time sequence of items. Streaming applications pose new and interesting challenges for data management systems. Such application domains require queries to be evaluated continuously as opposed to the one time evaluation of a query for traditional applications. Streaming data sets grow continuously and queries must be evaluated on such unbounded data sets. These, as well as other challenges, require a major rethink of almost all aspects of traditional database management systems to support streaming applications. Stream Data Management comprises eight invited chapters by researchers active in stream data management. The collected chapters provide exposition of algorithms, languages, as well as systems proposed and implemented for managing streaming data. Stream Data Management is designed to appeal to researchers or practitioners already involved in stream data management, as well as to those starting out in this area. This book is also suitable for graduate students in computer science interested in learning about stream data management.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites. Today, businesses are either migrating location-specific capabilities into their information systems, or expanding existing Geospatial Information Systems (GIS) implementation into enterprise-wide solutions. As enterprise information systems evolve toward service-oriented architecture (SOA), geospatial technologies also evolve along the same lines.Geospatial Services and Applications for the Internet covers a wide spectrum of techniques, algorithms and modeling methodologies that address the challenges in service-oriented architectural design for GIS, and intelligent processing for spatial queries. This book presents in-depth studies on performance improvement, data integration, service personalization and interoperation between geospatial services. These studies provide the reader with a wide spectrum of examples and case studies on the development of GIS for hydrological applications, electrical power supply applications, land usage and urban planning, and NASA’s Earth image datasets dissemination.Geospatial Services and Applications for the Internet is designed for a professional audience composed of practitioners and researchers in industry.  This book is also suitable as a secondary text book or reference for advanced-level students in computer science and geosciences.

Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing. Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science.