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Fenn s work on advanced technologies was a critical factor in defining the time line for technologies that govern the World Without Secrets. I am grateful to every interviewee who offered time and insight to me, including Eric Raymond, Susan Anderson, Alicia Peck, Bill Bodin, Chris Amenita, Chris Sagalyn, David Bernstein, Ken Watman, Tom Koloski, Len Hynds, Steve Millstein, Gary Wallace, Mary Jo Deering, Cynthia Baur, Marco Alpert, Max Brunswick, Nicos Peonides, Patty Casey, Victor Kovner, Terry Danner, Ron Sobel, Miles Copeland, Bill Todd, Frances Zelazny, Don Simmonds, David Reid, Neil Scott, Egil Juliussen, Richard Stallman, and Amy Ray. I ve been assisted throughout by Sandra Lahtinen, Dora Salm, and other members of Gartner s Information Resource Center, surely a worldclass research team. Michelle Henderson of Gartner Press assisted, in many ways, with smoothing over the bumps that tend to slow authors down. Finally, thanks to my wife, Patty, for her support, excitement in the work as it developed, and steely-eyed management of my time for the past six months. The World Without Secrets is a dynamic place, to say the least. For the latest updates and research, check the World Without Secrets Web site at http:/www.worldwithoutsecrets.com. / R.H.

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Spatial integration and mapping of these worlds onto each other may be dynamic and controlled, allowing application and internal system optimization problems to be solved coherently within the same space-conquering formalism. WAVE-WP also represents a higher level distributed processing and control model than its predecessor WAVE, allowing us to compose arbitrary space-processing expressions operating directly with remote data, the latter representing both information and physical matter or physical objects. We have given only a general, informal description of the WAVE-WP model, which will be further clari ed by a detailed description of WAVE-WP language in the following chapter.

In this book, numerous models have been provided that can help jump-start data modeling efforts. But what are the purposes for these models, and how can the enterprise use them to build higher-quality operational and data warehouse databases The models in this book, as well as those in Volume 2, can facilitate the building of more integrated systems, help the enterprise better manage its information, and can lead to higher-quality database designs in shorter periods of time. This chapter will cover the life cycle of the model from the development of an enterprise data model, to the development of the logical data model for a project, to the development of a physical database design which is the basis for implementing a database. Using these models for data warehouse implementations will also be discussed. Effective methods for incorporating the Universal Data Models can be summarized as follows: Develop the enterprise data model by customizing and adding to the Universal Data Models using the business terms that are commonly known in the enterprise and adding appropriate information requirements. Build the appropriate logical data models for each project according to the business requirements for that specific application.

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The following order model addresses these previous issues and provides a more flexible structure to maintain purchase and sales order information.

If we have more powerful boards of directors at nancial institutions, we should also make sure that shareholders have appropriate input into

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