| Abstract [eng] |
Topic Maps is knowledge representation and exchange model having rich verbalization possibilities for improving navigation-based search and understanding for human and also interpretable by machine. Despite increasing usage of Topic Maps in knowledge-based information networks and portals, the flexibility of representation often leads to disability to judge about correctness or completeness of a Topic Map model, or simply gives no rule how to model problematic actualities. The work presents the methodology for developing Topic Maps on the base of the principles of developing ontologies extending them with recommendations for solving some problems specific to Topic Maps development: creating normalized schema; representing association properties and names, multiple classification hierarchies, and so on. The suitability of the methodology is analyzed via a case study for developing Topic Map for representing information content with Ontopia tools. |
