Design and evaluation of overview components for effective semantic data exploration

• Authors: Josep Maria Brunetti
• Venue: Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics
• Year: 2013

The growing volumes of semantic data available in the Web result in the need for handling the Information Overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a dataset. The objective is that the user is capable of getting an idea about the overall structure of the dataset. However, obtaining this overview cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous datasets, which is typical in the Semantic Web. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new dataset. This can be a serious limitation when exploring a dataset for the first time, specially for lay-users. Our proposal is to reuse and adapt existing Information Architecture (IA) components to provide this overview to users. Such IA components are well known to Web users, as they are present in most web pages: navigation bars, site maps and site indexes. We complement them with treemaps, a visualization technique for displaying hierarchical data. We report about the design of these components as well as their evaluation with end-users performing real tasks.