Mapping is an essential consideration for two reasons. The first rationale for mapping is to create a consistent and coherent knowledge structure over which to reason and conduct machine learning. The second rationale is to consolidate local information resources, what is known as data integration. The easiest way to meet both of these rationales is to leverage off an existing knowledge structure, which itself is already proven to be logically consistent. This is the role that KBpedia plays. When extended with your local concepts and terminology, your enterprise extension of KBpedia now itself becomes a consistent structure for learning, tagging and categorization.
Here are some of the current use cases published by Cognonto relevant to mapping: