Ontology-based information model development for science information reuse and integration

Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, a set of principles, and a real world case study where shared ontologies are used to develop and manage science information models and subsequently guide the implementation of scientific digital libraries. The tool framework, based on an ontology modeling tool, has been used to formalize legacy information models as well as design new models. Within this framework, the information model remains relevant within changing domains and thereby promotes the interoperability, interconnectedness, and correlation desired by scientists.