Geographic information is critical for many earth related geo-science applications such as building disaster planning, crisis management, early-warning systems and urban planning. Decision making in Geographic Information Systems (GIS) increasingly relies on analyses of spatial data in map-based formats. Maps are complex structures composed of layers created from distributed heterogeneous data belonging to the separate organizations. This thesis presents a distributed service architecture for managing the production of knowledge from distributed collections of archived observations and simulation data through integrated data-views. Integrated views are defined by a federation service (?federator?) located on top of the standard service components. Common GIS standards enable the construction of this system. However, compliance requirements for interoperability, such as XML-encoded data and domain specific data characteristics, have costs and performance overhead. We investigate issues of combining standard compliance with performance. Although our framework is designed for GIS, we extend the principles and requirements to general science domains.
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Geographic information is critical for many earth related geo-science applications such as building disaster planning, crisis management, early-warning systems and urban planning. Decision making in Geographic Information Systems (GIS) increasingly relies on analyses of spatial data in map-based formats. Maps are complex structures composed of layers created from distributed heterogeneous data belonging to the separate organizations. This thesis presents a distributed service architecture for managing the production of knowledge from distributed collections of archived observations and simulation data through integrated data-views. Integrated views are defined by a federation service (?federator?) located on top of the standard service components. Common GIS standards enable the construction of this system. However, compliance requirements for interoperability, such as XML-encoded data and domain specific data characteristics, have costs and performance overhead. We investigate issues of combining standard compliance with performance. Although our framework is designed for GIS, we extend the principles and requirements to general science domains.
Ahmet Sayar has a Ph. D. from Indiana University Computer Science Department. He holds a master degree in Computer Science from Syracuse University and a Bsc. degree from Istanbul Technical University. His research interest is applications of Web technologies to problems in scientific computing and performance problems in distributed systems.
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Taschenbuch. Zustand: Neu. Neuware -Geographic information is critical for many earth related geo-science applications such as building disaster planning, crisis management, early-warning systems and urban planning. Decision making in Geographic Information Systems (GIS) increasingly relies on analyses of spatial data in map-based formats. Maps are complex structures composed of layers created from distributed heterogeneous data belonging to the separate organizations. This thesis presents a distributed service architecture for managing the production of knowledge from distributed collections of archived observations and simulation data through integrated data-views. Integrated views are defined by a federation service (¿federator¿) located on top of the standard service components. Common GIS standards enable the construction of this system. However, compliance requirements for interoperability, such as XML-encoded data and domain specific data characteristics, have costs and performance overhead. We investigate issues of combining standard compliance with performance. Although our framework is designed for GIS, we extend the principles and requirements to general science domains.Books on Demand GmbH, Überseering 33, 22297 Hamburg 192 pp. Englisch. Bestandsnummer des Verkäufers 9783838319339
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