We describe the architecture and implementation of the Solid Earth Research Virtual Observatory (SERVO)’s Complexity Computational Environment. We base our design on a globally scalable
distributed “cyber-infrastructure,” or Grid, built around a Web Services-based approach consistent with the extended Web Service Interoperability (WS-I+) model. In order to investigate problems in earthquake modeling and forecasting, we need to programmatically couple numerical simulation codes and data assimilation and mining tools to online observational data sets, including GPS stations, fault data, and seismic activity catalogs. These observational data sets are now available on-line in internet-accessible forms, and the quantity of this data is expected to grow explosively over the next decade. As part of our efforts in building SERVO, we are extending these online data repository capabilities so that they are not just available directly for human users, but may also
be searched, filtered, and streamed to simulation codes that are also managed by SERVO services.

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The Open Geospatial Consortium (OGC) [1] defines a number of standards, both for data models and for online services, that has been widely adopted in the Geographical Information System (GIS) community. This has lead to a number of software development efforts, online data archives, and application communities. The emergence of Web Service technique overcomes the shortcoming of
traditional Distributed Object technique and provides the interoperable capability of cross-platform and cross-language in distributed net environment. GIS services will be implemented more extensively by using Web Service approach. A spatial data infrastructure lets many GIS vendors share data stores and applications in a distributed environment. GIS basically involves the integration of data and services from multiple sources from different vendors. The Web services architecture establishes a standard interconnection rules between services and information clients that nicely support the dynamic integration of data, which is the key to creating a spatial data infrastructure. By introducing Web Services, distributed GIS services from different vendors can be dynamically integrated into the GIS applications using the interoperable standard communication protocols of the Web Services. To be able to benefit from the Web Services in the GIS applications, all the service providers should provide their services as Web Services. General acceptance from the vendors increases the interoperability and enhances the GIS applications. We find that the OGC
standards are very compatible with Web Services standards, although they are not technically implemented this way. To be able to benefit from Web Services technologies we have built a common architecture to convert any OGC GIS services to Web Services and applied this to our current WMS project.

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The Open Geospatial Consortium (OGC) defines a number of standards (both for data models and for online services) that have been widely adopted in the Geographical Information System (GIS) community. In this paper we will describe our group’s efforts to implement GIS services according to OGC standard specifications in accordance with the Web Services approach. This paper focuses on the Web Map Service (WMS), which we are coupling to problems in computational geophysics. Through the use of Web Services, we are able to integrate GIS services with other families of services, including information, data management, and remote application execution and management. We also describe WMS client building efforts that are suitable for integration with computational Web portals. To be able to interact with non-Web Service versions of WMS, we have built bridging service for our extended WMS. Since Web Service oriented WMS has a different request/response paradigm from non-Web Service versions, we have extended cascading WMS by adding request handler functionality. This kind of WMS behaves like both a cascading WMS and a proxy to handle different types of requests to overcome interoperability problems between different WMS systems.

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We discuss a general architectural approach to knowledge and information management and delivery in distributed systems. Our approach is based on the recognition that time-stamped, streaming information message units form the core of seemingly disparate systems that range from online sensors and scientific instruments to Web information retrieval. Globally distributable Grid services manage these information streams. Geographical Information System services provide exemplary realizations of this picture and may be used as a model for other scientific domains. With this unified architecture in place, we may begin to consider the problems of information integration as equivalent to sensor federation.

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