We have seen seven patterns emerge, all of which are powerful and take advantage of ArcGIS Server.
1. Web Mapping. This pattern involves browser clients using ArcGIS Server map services. ArcGIS supports two methods for Web mapping:
The latter offers many benefits including continuous pan, zoom, and roam. Many of our users are caching some of their data (e.g., basemaps) while serving their operational data (data that frequently changes) dynamically. With ArcGIS 9.3, the ability to create and update a cache has been simplified.
2. Web GIS. This pattern involves an integration of GIS servers with desktops, browsers, mobile devices, and other Web applications to deliver GIS over the Web or a network. It supports the idea of authoring geoprocessing models as well as maps and publishing them as services that can be easily consumed by a variety of client applications. This pattern distributes GIS capabilities such as mapping, analysis, and editing to where they’re needed in the most effective manner. This pattern is well suited to organizations that require a variety of standard applications, but also supports the ad hoc consumption of multiple data resources and distributed services.
3. Enterprise Infrastructure. In this pattern, the server works with other IT systems such as CRM, ERP, etc. In this architecture, ArcGIS is ideally designed to integrate services (such as mapping, geocoding, spatial analysis, etc.) with other database services typical in business systems. Customers of this pattern may not realize that GIS servers are facilitating their workflows or that spatial analysis is a component of the applications they use.
4. Mobile. In this pattern, ArcGIS Server provides the back office and collaboration services for ArcGIS Mobile clients. Under this scenario, mobile clients receive GIS maps and data services and can also use and edit this data in a traditional field based workflow (i.e., inspection, data collection, etc.). This pattern also supports the integration of field observation data into a central environment to provide situational awareness. This pattern is particularly appropriate for emergency management and monitoring and managing field workers in organizations where a considerable amount of the work is done in the field. The mobile services scenario is an emerging pattern for ESRI, and we believe it promises to be a rich way to disseminate GIS in the future.
5. Spatial Data Infrastructure. This pattern involves a distributed network of servers that supply each other with transactional information. For example, a city planning department, an engineering department, and a land information department can each maintain their own information sets (layers) on their own workgroup servers. At the same time, they can serve this information to their colleagues for use in other departments. An enterprise server is used to replicate the information in each departmental server for cross-enterprise applications and perhaps for sharing this information across the enterprise or publicly via the Web.
This architecture works at all different scales and within various types of organizations. For example, cities, counties, states, and federal governments can operate using the same concepts. Likewise, relationships among organizations (at different levels of government and between different types of institutions) are possible.
6. Data Fusion Center. This pattern involves bringing copies of all the distributed geographic data belonging to a network of GIS organizations together into a central server. Data is typically copied into an organized data warehouse supporting a series of high performance focused applications. Another name for a data fusion center is a “geo-warehouse” - an integrated warehouse for bringing all the geospatial data together. The concept of a geo-warehouse involves taking all the real data in its native formats and organizing it for high performance applications. The idea is to fuse data for applications such as emergency management.
The data fusion centers that are being developed within each state in accordance with a mandate from the Department of Homeland Security provides an example of these sorts of systems. The State of New York has created such a system to bring its homeland security data from hundreds of state and local agencies into a single high performance environment. This data is then served via the Web, providing information to support emergency response.
We believe this pattern will be extensively deployed for emergency management in homeland security and defense/intel organizations. We also see the opportunity for fusion centers to provide a new way to bring community information together in support of a community Website.
7. Mashups. Mashups are a technology-based concept for the Web 2.0 environment. A mashup is a Web application that combines data from more than one source into a single integrated tool.
Mashups are facilitated by using JavaScript tools that provide simple ways to integrate multiple Web services into an application. Underlying the concept of mashups is the ability to script together URL addresses and connect data being served at these addresses into a mashup application.
ArcGIS users will find the mashup pattern to be extremely valuable for creating quick and easy applications that blend services from different ArcGIS Servers with virtually any kind of information on the Web.
Summary. It's our view that all seven of these patterns will be used by our user community in various combinations. Users will build Web GIS with map services, mobile connections, and mashups. They will then replicate it in enterprise servers or data fusion centers and integrate this technology into enterprise environments.
These patterns will become a vocabulary for system designers to create solutions. They represent templates of best practices that can be creatively leveraged by system designers, architects, and the general GIS profession.
We encourage our users to study these patterns carefully because they provide the foundation for the new ways that we can use GIS on the Web.
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