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Data Development and Evolution
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Have Data, Will Travel: A Data-Centric Approach to Enterprise Systems Development
John A. Zumbado
GeorgiaPowerCompany
241 RalphMcGillBlvd., Bin 20020
Atlanta,GA30144-3374
Email: jazumbad@southemco.com
PhillipA. Naecker
GatekeeperSystems,Inc.
1010E. UnionStreet, Suite 101
Pasadena,CA9110-69756
Email:pan@gatekeeper.com
WilliamH. Iller
OrbitalImagingSystems, 21700AtlanticBlvd.
Dunes,VA20166
Email:mailto:iler.bill@orbital.com
Introduction-The Data Centric Approach Applied To AM/FM/GIS
The development of a large AM/FM/GIS system is always a challenge. Such systems often involve
a large number of diverse data sources, with complex interrelationships between the data elements.
These data sources typically include those both internal and external to the enterprise. Moreover,
AM/FM/GIS systems are often burdened with very broad application requirements, including
complex spatial analysis and display operations.
To make matters more difficult, large AM/FM/GIS systems often involve interaction between
multiple-user departments and support organizations. Traditional application requirement
definition and deployment approaches involve extended requirements gathering, business process
reengineering, infrastructure upgrades, and a plethora of other activities. The result is typically a
lengthy development process fraught with delayed deployment of critical information systems.
These delays often result in a failed or much under-delivered project.
This paper describes an approach that enables the rapid development and deployment of
AM/FM/GIS systems capabilities in the face of such challenges. This approach has been
successfully used in implementing large-scale, enterprise-wide AM/FM/GIS projects in very short
timeframes.
The data-centric approach, as this new methodology has been dubbed, focuses principal attention
on delivery of geospatial data and related tabular data to end users rather than providing new
geospatial data or new geospatial analysis applications. This approach concentrates on identifying,
collecting, coordinating, and linking together enterprise data resources, and then providing the
widest possible access to this spatially enabled data via Internet tools. The business driver for this
approach is that properly organized data has tremendous value to workers throughout an enterprise.
Organizations gain business value by quickly providing data access instead of waiting for the
development and implementation of complex applications. With the data in place and accessible,
increasingly complex applications can evolve as the business need is identified and addressed.
The principal components of the data-centric approach are:
- Bringing the data together
Oneofthe great stumbling blocks forlarge AM/FM/GIS
applications is the management of heterogeneous and distributed geospatial and related tabular
datasets that are under the control of disparate departments or external organizations. In the
data-centric approach, all datasets are brought together and linked, in a single common
environment convenient for "publishing" on the Internet or Intranet ("links" are both literal
Web hyperlinks and less literal connections between data sources). Thus, the problem of online,
realtime integration of multiple disparate datasets is reduced to a series of easily built and
easily maintained data import efforts.
- Staying focused on the
data
Significant value within the enterprise is gained from existing
geospatial and tabular data by exploiting the linkages created between the data sets. These
linkages spatially-enable the tabular data sets, which facilitates spatial data integration and
presentation. In order to gain this value quickly, the focus of a project must be kept on
deploying the data, and the temptation to jump into developing some new application
functionality.
- Leveraging Internet tools and availability
Using widely available and free (or nearly free)
Internet technologies, the newly organized data can be deployed as widely as possible. The
entire enterprise is given access to the data, because the only tools required are Internet
browsers with free or very inexpensive plugins. Because this initial access application is based
on familiar browser user interfaces, training requirements are minimal or non-existant. This
and subsequent applications self-install, and can be updated and extended without revisiting
any desktops and generally without retraining.
- Adding more applications
Even if the data is easy to
access, there will be needs for applications to help the users interact
with the data in more efficient and powerful ways. In the data-centric
approach, such applications are developed in parallel with and
secondarily to the data management task. Because the data has already
been widely deployed over the Intranet/Internet in an easy-to-use
environment, applications that follow can build upon a rich data
environment and be more focused on specific, narrow tasks. Most
importantly, application development is freed of the often complex and
time-consuming tasks of providing data navigation tools, creating a
deployment platform, and creating links to other datasets. Those
activities have already been solved by the preceding data management and
publishing tasks.
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