The most valuable information an organization has resides in the brains of its employees. Knowledge management provides a means of capturing, preserving, sharing and reusing that information. Inevitably each employee will retire, change jobs, win the lottery, or leave the organization for some other reason. Knowledge management allows your organization to continue functioning at the highest level even after key players leave. Preserving and managing knowledge is vital to an organization's ongoing success.
Of the many technology advances taking place today, semantic technologies stand out for their orientation and promise. Semantic technologies make it possible for machines to draw many of the inferences that humans make every day and mostly take for granted. This means that semantic technologies provide the best mechanism today for knowledge management.
While it may sound like magic or science fiction, semantic technologies are neither. What they are, in fact, is an ideal means of capturing and using the knowledge that companies routinely build up in their workforce and then lose as workers move on to other jobs or retire.
The opportunity is two-fold:
- to develop a knowledge base by capturing and retaining that knowledge.
- then building on it over time through normal growth and machine-based inferencing.
The primary means for achieving all this is through an ontology which captures a specific amount of knowledge of a domain. Ontologies can be submitted to a reasoner so that inferences may be drawn.
Semantic technologies are built around the academic discipline of Description Logics and the collection of RDF/OWL standards from the W3C. That gives semantic technologies an unusually strong opportunity to make progress in the marketplace; academic research is rich and steadily contributing to the development of the field, while the standardization of the technology allows companies to build semantic solutions in confidence that their work will inter operate with other semantic tools.
Semantic technologies can be used in a number of ways, each of which complement that others:
- Integration
- Enterprise Search
- SCORM Learning Modules
- Text Analytics Applications
At last, the many applications that use all the different kinds of knowledge represented in each of these find a common expression; companies can now build applications and processes that truly integrate these different areas and become the informational backbone of the enterprise.