Information processing technologies are a modern marvel. As Peter Drucker noted, computing infrastructures have helped us to accomplish many tasks quickly and in high volume. Furthermore, with the widespread availability of the Internet, computers support unprecedented levels of communication -- both to the masses and on an individual level.

 

As Drucker also indicated, computers don't particularly improve our ability to extend process-related knowledge. He indicated that this had been a surprise to him at the end of the 20th Century and others who had predicted otherwise when computers began to be generally available in the 1950s. Computers have shown to help us to collaborate in the creation of static forms of knowledge, though. The challenge of our age is in the conversion of static forms of knowledge to expressive, process-related knowledge forms that can lead people through the steps of a process. This is a critical factor in providing us with the capacity to break through the issues of head, hand, and heart that constrain our organizations.

 

The head and the heart aside, new information processing approaches belong in the realm of the hand. This is to say, they must work. They must prove efficient. They must be demonstrable. They must pass tests imposed by engineers and accountants and technologists that don't particularly care for issues of logic or of the heart.

 

Generative taxonomies provide a means of creating and linking static and process-related knowledge representations. Based on Aristotle's principal knowledge form -- 'if p, then q' -- generative taxonomies lead logic designers and users step by step through a process in similar fashion to what musicians do as they progress measure by measure through fixed compositions of classical performers or 'ad lib' sets of jazz artists or popular performers.

 

Organizational logic embodies different challenges than faced by musicians. They must conquer issues of space and time. From a collaborative standpoint, they must support more complex collections of activities by more diverse actors than is typically the case with musicians. They probably face greater challenges in maintaining currency. These factors must be considered in the establishment of information processing, or common language norms.

 

In seminars, we present the generative taxonomy model as a means of achieving similar objectives as those realized by musicians, but in light of the information processing needs of organizations and social networks. As part of this process, we have included presentations by biologists  and a manufacturing specialist. These individuals have demonstrate the generative taxonomy model using two examples in their areas of research and practice. The point is to understand the groundings in the generative taxonomy model, how its simple structure enhances its ability to express complexity.