Describing a Knowledge Field with Topic Maps
Abstract
Semantic web technologies are not focus intrinsically to the terms describing a scientific field but extend further towards meaningful relationships, a task that in traditional systems of knowledge representation is allocated to humans. In a standard approach the most valuable tool in the study and comprehension of a scientific disciple is the concept map. This map is a well-structured and classifiable graph that represents scientific information optically. Evolution of this representation in the knowledge organization systems are the Topic Maps. In Topic Maps the different concepts are hierarchical and relational connected in a virtual map, while URIs ensure the interoperability of this form of ontology. Topic Maps allow to the developer a high degree of expressiveness, especially in the case of multidimensional relationships. Herein, we generated a Topic Map for the Cardiology field, using a minimum but sufficient set of terms to cover almost 70% of cardiovascular terminology. Cardiology is in focus because the cardiological disorders remain the first cause of morbidity and mortality worldwide, while the available semantic description systems for this field are limited. We build an experimental cardiological ontology by utilizing XAMPP, Topincs, Wandora and Ontopia as developmental tools. The resulting map is currently under evaluation and enrichment to include in addition to the clinical entities, cell biology, implantable instruments, and pharmaceuticals. We anticipate that in future this tool would be a valuable addition in information science and cardiology which will assist both clinical and experimental scientists.
