Building Semantic Tools for Concept-based Learning Spaces: Knowledge Bases of Strongly-Structured Models for Scientific Concepts in Advanced Digital Libraries

Terence R. Smith, Marcia L. Zeng

Abstract


Applying conventional principles of knowledge organization, representation, and other semantic tools, we have constructed a model for scientific concepts and employed knowledge bases and visualization tools to represent knowledge concerning scientific concepts. Strongly-structured models, such as the integration of a taxonomy (or thesaurus) with metadata (or attribute-value pairs) and domain-specific markup languages, as well as specialized models for learning scientific concepts, focus on such attributes as objective representations, operational semantics, use, and interrelationships of concepts. All of these play important roles in constructing representations of knowledge in most domains of science. Instructional activities for undergraduate teaching and learning are greatly facilitated with the use of such integrated semantic tools.

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