Intuitive Ontology-Based SPARQL Queries for RDF Data Exploration

This paper introduces a strategy for both the retrieval and analysis of linked open data (LOD) based on the use of visual tools. Retrieving and understanding data from triplestores (such as SPARQL) requires technical knowledge and proves to be challenging with large datasets, which result in an increase in the mental overload when unknown ontologies are involved in the creation of complex queries. These two problems benefit greatly from visual techniques that allow for executing them in an easier and more intuitive manner. These techniques have already been applied to each problem separately; however, we propose combining them to lower the complexity of triple-store data retrieval and empower its exploration and analysis through specific data visualizations. To demonstrate the suitability of this strategy, a web-based tool was implemented. It allows for the creation of interactive queries using node-link ontology representations, and a subsequent filtering and analysis through a configurable dashboard with different data visualizations. This paper also presents a user-centred design process and evaluation of the proposed tool.