Knowledge Management in Large Organizations

Abstract

This chapter provides an overview of the knowledge management (KM) problems, and opportunities, faced by large organizations, and indeed also shared by some smaller organizations. The chapter shows how semantic technologies can make a contribution. It looks at the key application areas: finding and organizing information; sharing knowledge; supporting processes, in particular informal processes; information integration; extracting knowledge from unstructured information; and finally sharing and reusing knowledge across organizations. In each application area, the chapter describes some solutions, either currently available or being researched. This is done to provide examples of what is possible rather than to provide a comprehensive list. The chapter also describes some of the technologies which contribute to these solutions; for example, text mining for analyzing documents or text within documents; and natural language processing for analyzing language itself and, for example, identifying named entities. Most fundamentally, the use of ontologies as a form of knowledge representation underlies everything talked about in the chapter. Ontologies offer great expressive power; they provide enormous flexibility, with the ability to evolve dynamically unlike database schema; and they make possible machine reasoning. The chapter concludes by identifying the key trends and describing the key challenges to be faced in the development of more powerful tools to support knowledge work.