Context & Dynamic Context

Semantics must be able to support analysis as well as application interoperability.Context represents our most powerful analytic mechanism. Generically, Context refers to the specific perspective ofany group, individual or entity in regards to any combination of Semantic information. Dynamic Context takes this astep further by combining any given Context with a unique point in time. The reason for this is clear, Context is not a permanent state; perspectives change with time. The only way to accurately determine true Context is to capture it in its relative state. Context can also be tracked across time to illustrate the evolution of any given perspective.

The reason that most data standardization efforts have failed in IT is that unless one is working in a highly controlled environment, differing Contexts cannot be accommodated. Ultimately, someone or some group always feels left out and in fact they are. When dealing with information across hundreds, thousands or even millions of users or organizations, traditional data standardization methods and techniques can never hope reconcile the differences and support interoperability on a global scale. If Context or Dynamic Context is understood we can then determine how to construct Dynamic Sets that allow us to Interact with Shared Formal Sets. The future of all integration may very well become centered around the creation of Dynamic Sets and Dynamic Semantic Rules. These tools will determine the exact information (structured and unstructured) and logic we may need to accomplish any given task, answer any given question or solve any given problem.

Copyright 2008, Semantech Inc.