Qualifying Ontology-Based Visual Query Formulation

Abstract. This paper elaborates on ontology-based end-user visual query formulation, particularly for users who otherwise cannot/do not desire to use formal textual query languages to retrieve data due to the lack of technical knowledge and skills. Then, it provides a set of quality attributes and features, primarily elicited via a series of industrial end-user workshops and user studies carried out in the course of an industrial EU project, to guide the design and development of successor visual query systems

Towards exploiting query history for adaptive ontology-based visual query formulation

Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed