Modeling a description logic vocabulary for cancer research.

The National Cancer Institute has developed the NCI Thesaurus, a biomedical vocabulary for cancer research, covering terminology across a wide range of cancer research domains. A major design goal of the NCI Thesaurus is to facilitate translational research. We describe: the features of Ontylog, a description logic used to build NCI Thesaurus; our methodology for enhancing the terminology through collaboration between ontologists and domain experts, and for addressing certain real world challenges arising in modeling the Thesaurus; and finally, we describe the conversion of NCI Thesaurus from Ontylog into Web Ontology Language Lite. Ontylog has proven well suited for constructing big biomedical vocabularies. We have capitalized on the Ontylog constructs Kind and Role in the collaboration process described in this paper to facilitate communication between ontologists and domain experts. The artifacts and processes developed by NCI for collaboration may be useful in other biomedical terminology development efforts.

Enhancing quality of retrieval through concept edit history.

The NCI Thesaurus is a public domain description logic-based terminology produced by the National Cancer Institute. The NCI Thesaurus is used to support storage and retrieval of scientific, clinical and research administration data. The content of the NCI Thesaurus evolves rapidly. We have developed a representation of concept change over time and have implemented software to capture concept change in our multi-editor concurrent vocabulary development environment. We are now implementing software to extend our vocabulary server, public APIs and our file-based distributions of the Thesaurus to provide access to the concept-level history information.

Role grouping as an extension to the description logic of Ontylog, motivated by concept modeling in SNOMED.

Several clinical terminologies now utilize description logic to model the logical definitions of concepts. Recent editions of the Systematized Nomenclature of Medicine (SNOMED) have been developed using the description logic Ontylog. A significant design criterion for SNOMED is to keep concept expressions simple enough to be broadly usable by clinicians, while maintaining faithful representation of concept meaning. Motivated by this criterion, "role grouping" has been developed as an extension to the description logic Ontylog. This paper describes the problems that motivated the creation of role grouping, outlines the semantics of role grouping, illustrates the benefits of this construct with examples from SNOMED Clinical Terms, and provides an algorithm for determining normal forms for expressions involving role groups.