Currently browsing: Items authored or edited by Paul Warren

Warren, Paul and Mulholland, Paul (2020). A comparison of the cognitive difficulties posed by SPARQL query constructs. In: Knowledge Engineering and Knowledge Management. EKAW 2020. Lecture Notes in Computer Science, vol 12387 (Keet, C. M. and Dumontier, M. eds.), Springer, Cham, pp. 3–19.

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Warren, Paul; Mulholland, Paul; Collins, Trevor and Motta, Enrico (2019). Improving comprehension of Knowledge Representation languages: a case study with Description Logics. International Journal of Human-Computer Studies, 122 pp. 145–167.

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Warren, Paul and Mulholland, Paul (2018). Using SPARQL – the practitioners’ viewpoint. In: International Conference on Knowledge Engineering and Knowledge Management Proceedings (EKAW 2018) (Zucker, Catherine and Ghidini, Chiara eds.), Springer-Verlag, 11313 pp. 485–500.

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Warren, Paul (2017). Human Reasoning and Description Logics: Applying Psychological Theory to Understand and Improve the Usability of Description Logics. PhD thesis The Open University.

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Warren, Paul; Mulholland, Paul; Collins, Trevor and Motta, Enrico (2017). Using Insights from Psychology and Language to Improve How People Reason with Description Logics. In: The Semantic Web. ESWC 2017. Lecture Notes in Computer Science, vol 10249. (Blomqvist, E.; Maynard, D.; Gangemi, A.; Hoekstra, R.; Hitzler, P. and Hartig, O. eds.), Springer, Cham, pp. 465–481.

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Warren, Paul; Mulholland, Paul; Collins, Trevor and Motta, Enrico (2015). Making sense of description logics. In: Semantics '15: Proceedings of the 11th International Conference on Semantic Systems, ACM, pp. 49–56.

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Warren, Paul; Mulholland, Paul; Collins, Trevor and Motta, Enrico (2014). The usability of description logics: understanding the cognitive difficulties presented by description logics. In: The Semantic Web: Trends and Challenges, Lecture Notes in Computer Science, Springer, pp. 550–564.

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Warren, Paul; Mulholland, Paul; Collins, Trevor and Motta, Enrico (2014). Using ontologies: understanding the user experience. In: Knowledge Engineering and Knowledge Management, Lecture Notes in Computer Science, Springer, pp. 579–590.

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