The research aims at developing an integrated set of ontological conventions that addresses the needs of experimental sciences. In the researchersO earlier work in developing knowledge models for experimental biology, it was discovered that there were several important areas where the knowledge to be represented poses fundamental challenges to standard ontological frameworks. For example: 1) the traditional part-of hierarchy is ill-suited to model the complex substances and mixtures described in scientific experiments; 2) the primacy of categorization in knowledge representation, which fundamentally defines entities in terms of category membership, is at odds with the need to represent events (such as biochemical reactions) that convert one substance into another. The proposed research will improve the likelihood that ongoing artificial intelligence in knowledge sharing technology will be of benefit to researchers in experimental sciences.
