Inference of queries from their output examples has been extensively studied in multiple contexts as means to ease the formulation of queries. In this paper we propose a novel approach for the problem, based on provenance. The idea is to use provenance in two manners: first as an additional information that is associated with the given examples and explains their rationale; and then again as a way to show users a description of the difference between candidate queries, prompting their feedback. We have implemented the framework in the context of simple graph patterns and union thereof, and demonstrate its effectiveness in the context of multiple ontologies.

We propose to demonstrate QuestPro, a prototype interactive system aimed at allowing non-expert users to specify SPARQL queries. Notably, QuestPro makes an extensive use of provenance in deriving the SPARQL queries, in two ways. First, we ask users to provide example output nodes along with explanations that are then treated as the provenance of the underlying query, guiding the system's search for a fitting query. We have designed an intuitive interface through which users can gradually build their explanations while understanding the connections between the different objects. The system then generates a set of candidate queries and uses provenance to explain each candidate, prompting user feedback to choose between them. We will demonstrate the usability of QuestPro using an ontology of academic publications, engaging the audience in the interactive process while explaining the under-the-hood model and algorithms.