Investigating Learnability, User Performance, and Preferences of the Path Query Language SemwidgQL Compared to SPARQL

Stegemann, T., & Ziegler, J. (2017). In C. d’Amato, M. Fernandez, V. Tamma, F. Lecue, P. Cudré-Mauroux, J. Sequeda, C. Lange, & J. Heflin (Eds.), The Semantic Web – ISWC 2017: 16th International Semantic Web Conference, Vienna, Austria, October 21–25, 2017, Proceedings, Part I (pp. 611–627). Springer International Publishing.


In this paper, we present an empirical comparison of user performance and perceived usability for Sparql versus SemwidgQL, a path-oriented Rdf query language. We developed SemwidgQL to facilitate the formulation of Rdf queries and to enable non-specialist developers and web authors to integrate Linked Data and other semantic data sources into standard web applications. We performed a user study in which participants wrote a set of queries in both languages. We measured both objective performance as well as subjective responses to a set of questionnaire items. Results indicate that SemwidgQL is easier to learn, more efficient, and preferred by learners. To assess the applicability of SemwidgQL in real applications, we analyzed its expressiveness based on a large corpus of observed Sparql queries, showing that the language covers more than 90% of the typical queries performed on Linked Data.


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