Geographic information systems (GIS) play a role in the process of solving critical business problems in industries such as government, utilities, retail, banking, insurance, oil and gas, transportation, and health. Gathering and summarizing information about the geographic location and the movement of core business elements is essential to the operation of today's enterprises. These elements could include products, assets, or services within a commercial or government entity. Examples such as supply chain management, land management, field service delivery, and emergency response all demonstrate the importance of location information. This IBM® Redpaper describes key components of an enterprise GIS. We focus on the interface between ESRI ArcGIS and IBM WebSphere® Application Server, where WebSphere Portal Server is deployed. We explore the integration of ArcGIS Server 9.1 and 9.2 within the WebSphere 6.0 framework. The major subsystems are described and programming examples are provided, using the Java™ 2 Enterprise Edition (J2EE™ ) application programming language.

When tuning a database for better performance, one area to examine is the proximity of the database to the application. Can the database be located on the same server as the application? Will a database server located far away from the application server cause performance degradation? To answer these questions, we conducted a series of measurements at the IBM zSeries Benchmark Center to determine performance impact based on the distance between the application and database servers. This paper discusses the results of our tests.

IBM Data Discovery and Query Builder is a query application development environment built on IBM DB2 and WebSphere technology. Data Discovery and Query Builder enables the creation of applications to let users build complex queries without dealing with the details concerning the physical location and representation of the information being queried. Now proven in multiple IBM Life Sciences customer engagements, physicians, scientists, and researchers without information technology expertise are using Data Discovery and Query Builder to construct queries that explore critical research areas, such as discovering links between diseases and patient behavior. This IBM Redpaper describes how developers can create applications extending the Data Discovery and Query Builder framework through the implementation of plug-ins. This paper guides the reader through a set of sample scenarios that complement the reference documentation provided by the product's JavaDocs. The information in this paper will help Java developers to understand how to implement Data Discovery and Query Builder plug-ins. This Redpaper provides an overview of the available plug-ins and includes implementation examples for each plug-in available with Data Discovery and Query Builder Version 1.1.