Using Chained Views and Follow-Up Queries to Assist the Visual Exploration of the Web of Big Linked Data
Aline Menin, Minh Nhat Do, Carla Maria Dal Sasso Freitas, Olivier Corby, Catherine Faron Zucker, Alain Giboin, Marco A. A. Winckler · International Journal of Human-Computer Interaction · 2022
The Web of Linked Open Data (LOD) provides access to a great number of dynamic datasets containing valuable information to support decision-making processes in diverse application domains while being publicly accessible and up-to-date. While information visualization techniques are useful to explore, analyze, and explain relationships within LOD data, the existing tools are limited to visualizing a single dataset at a time and, often, use static and preprocessed data. In this article, we leverage the linked aspect of LOD to support the dynamic integration of data into a visualization system by connecting views and distributed LOD datasets using the so-called follow-up queries. We demonstrate how our approach uses dynamic SPARQL queries to integrate external data into the exploration flow through visualization techniques and enrich the ongoing analysis. We ran a semi-structured interview to assess the usefulness of our approach, which results were encouraging while showing its relevance to explore big linked data.