Modeling and navigation of large information spaces: a semantics based approach

We present techniques for modeling the semantics of large information spaces and for navigating them. This information space represents heterogeneous data stored in different formats and distributed across multiple locations on the Internet. We also describe a prototype system called SEMQUEST (SEMantics based QUEry SysTem) that employs graph-based algorithms and allows users to interactively explore, manipulate and relate data in large information spaces to their interests. It provides users with the flexibility to understand what is available in the information space, determine which parts are relevant, and query/retrieve underlying data using a visual framework. SEMQUEST also allows users to share software modules permitting them to reuse data analysis/visualization codes. We demonstrate system use with global climate change data collected by centers across the world. We believe this research serves as a foundation for future work in integrating information sources across the WWW.