Knowledge representation considerations for integration of diagnostic maturation information

With increasing frequency engineers, systems analysts, and software application developers are obliged to quickly acquire broad-based knowledge in unfamiliar information domains. Often requisite information sources are embodied in a stream of open source data, such as a network of World Wide Web sites or a proprietary customer document or data repository. When this occurs, the principal impediment to extracting relevant information can be the sheer volume of data that must be navigated and interpreted. This paper discusses some of the considerations in choosing suitable knowledge representations for use in the acquisition, integration, and analysis of diagnostic maturation information.