User-centered design and evaluation of overview components for semantic data exploration

Josep Maria Brunetti, Roberto García, Fran Alexander and Dr Ulrike Spree
2014 Aslib Journal of Information Management  
Structure Abstract Purpose. 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. Design/methodology/approach. The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand"
more » ... sed 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. Different Information Architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings. The chosen 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. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value. Obtaining semantic datasets overviews 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, because traditional Information Architecture techniques do not easily scale to large datasets. This can be a serious limitation when exploring a dataset for the first time, especially for lay-users. Our proposal is to reuse and adapt existing Information Architecture (IA) components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.
doi:10.1108/ajim-12-2013-0153 fatcat:rfftdnptobfj5j5u5cqks7azsq