Adding Value of Car Navigation- Visual Approaches to Knowledge Discovery

Car navigation systems are discussed in this study in terms of knowledge discovery, data mining and data quality. Since data, information and knowledge are inseparable levels of human cognition, integration of these methods aids to understand the real-world patterns for car navigation systems and add value. The car navigation system is multi-purpose, multi-scale, multi-temporal and varying users requires different levels of abstraction and visualization of spatial data and information. Hence, the data discovered, mined and the quality should be visualized on timely manner, without leading any confusing and for varying users and purposes. In this concept whole process was evaluated with in the context of research questions asked by Gahagen et.al (2001), where visualization problems and proposal for them were emphasized.