author guidelinesfor8（guidelinesfor8 author）.doc

SensorGrid: High Performance Web Service Architecture for Geographic Information Systems Galip Aydin 1. Geographic Information Systems Advances in Internet and distributed systems helped academia, governments and businesses to gain access to substantial amount of data, including geospatial data. However several significant problems cause limitations general users or applications to easily access and assimilate geospatial data. We note these limitations as following: Lack of universal standards: Over the years organizations have produced geospatial data in proprietary formats and developed services by adhering to different methodologies, Distributed nature of geospatial data: Because the data sources are owned and operated by individual groups or organizations, geospatial data is in vastly distributed repositories, Lack of interoperable services: Computational resources used to analyze geospatial data are also distributed and they lack the ability to be integrated when necessary. Traditionally geospatial data analysis starts with assembling required data from repositories and involves experts extracting information from it with the help of specialized applications. This mode of operation is significantly expensive as it requires specialized applications, sufficient resources for accommodating and analyzing large volumes of data, and experts to analyze it. Additionally, most of the data collected so far have never been analyzed because of the large volumes of input. As a result Geographic Information Systems (GIS) community lacks the advantages that might have been gained from understanding the available geospatial data products. We identify several problems with traditional approach: Problems with assembling data: Because of the distributed nature of geospatial data, users are required to utilize different tools to access data in various FTP or HTTP servers, relational or XML databases etc. In addition to the archived data real-time data providers employ di