Quality not Quantity! A Qualitative Evaluation and Proposal for Understanding the Depth of Audience “Knowledge” Post Data Extraction

Knowledge is defined as…the result of machine extracted patterns; humans making sense of their environment; information generated and aggregated from software services or as the lowest form of human cognition. Different perspectives, different domains, but one concept. Information scientists are often concerned with retrieving knowledge from data sources and sharing that knowledge with concerned stakeholders; with such differing views on what qualifies as knowledge a cross-domain approach might prove beneficial. This work is a qualitative assessment of the layers of knowledge intended to bridge the gap between the analyst and their intended or unintended audiences. It examines the benefit of abstracting concepts used in the education discipline to justify including a post-evaluation stage to the Knowledge Discovered through Databases (KDD) framework. It also intends to promote awareness of the various human cognitive capacities and provide a useful approach for communicating and evaluating machine-extracted knowledge that supports higher order thinking.