Knowledge discovery using the Tech OASIS: meeting the information infrastructure needs

Abstract

Summary form only given. Management decisions, generally, rely on corporate knowledge infrastructures, which most often are based solely on subject area expert knowledge, insights and recommendations. Expert opinions, formal and informal researcher, network interactions, and focused research literature reviews, along with actual R&D experiences, create the corporate knowledge base. The accelerated pace of research innovations, and the expanding accessibility of technology documentation have made this knowledge infrastructure process model inefficient and sub-optimal in respect to fully exploiting the available R&D information. Analytical techniques for knowledge discovery in large databases (KDD) offer the opportunity to improve the efficiency and effectiveness of organizations' knowledge infrastructures. However, the use of KDD tools, specifically the Technology Opportunities Analysis of Scientific Information System (Tech OASIS) addressed in this paper, requires an understanding of a cadre of new tools. These tools are based on statistical analyses, text mining and bibliometric measures, which are founded on concepts of how the technological innovation process works. Most often, technology subject matter experts and R&D managers have no time for developing this new skill set, thereby creating apathy toward KDD concepts and resistance to implementation. Implementation of this new technology, KDD, therefore, requires original approaches to gain user infrastructure acceptance, even as the technology itself is being developed.