SemUI: A Knowledge Driven Visualization of Diversified Data

The intrinsic diversity in Open Data affects its intuitiveness and acceptance from the end users' perspective. Existing tools lack efficient and effective mechanisms for handling diversified data, both in terms of content and presentation. Furthermore, users face difficulties in managing a large variety of data on their own. Thus, a standard methodology for data modeling, presentation and interaction is imperative in order to ease access and manage Open Data. We propose a solution and a tool named SemUI based on an integrated multi-tiered approach where: 1) a semantic layer integrates the data using the notion of real world entity and categorizes them according to their similarities and differences and, 2) a visualization layer which simultaneously shows multiple views based on the different properties of entities. Our evaluation result shows the feasibility of our approach by successfully accommodating the diversity in the data and thus providing a positive experience to the end users.