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Intuitive Ontology Authoring Using Controlled Natural Language

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Intuitive Ontology Authoring using Controlled Natural Language Ronald Denaux Submitted in accordance with the requirements for the degree of Doctor of Philosophy University of Leeds School of Computing February 2013 The candidate confirms that the work submitted is his/her own, except where work which has formed part of jointly authored publications has been included. The contribution of the candidate and the other au- thors to this work has been explicitly indicated below. The candidate confirms that appropriate credit has been given within the thesis where reference has been made to the work of others. Chapter 2, the background literature, is based on: R. Denaux, C. Dolbear, G. Hart, V. Dimitrova, and A. G. Cohn, Supporting domain experts to construct conceptual ontologies: A holistic approach, Web Semantics: Science, Services and Agents on the World Wide Web, vol. 9, no. 2, pp. 113-127, Jul. 2011. The original background literature for this paper was based on my own work and the Chapter in the thesis updates and goes into more detail about the related work. The technical description of ROOin Chapter 3 is based on: R. Denaux, V. Dimitrova, A. Cohn, C. Dolbear, and G. Hart, Rabbit to OWL: Ontology Au- thoring with a CNL-Based Tool, in Controlled Natural Language, vol. 5972, N. Fuchs, Ed. Springer Berlin / Heidelberg, 2010, pp. 246-264. This paper was mostly written by me, and reviewed and improved by the other authors. The design of the Rabbit controlled natural language and the Kanga methodology was done by the Ordnance Survey (C. Dolbear and G. Hart). An initial Rab- bit BNF was also done by the Ordnance Survey. I implemented the Rabbit parser on my own. During the implementation of the parser I updated the Rabbit BNF where necessary in collaboration with G. Hart. The initial design of ROO and the guide dog functionality was done in collaboration with Ordnance Survey and V. Dimitrova. The implementation of ROOand the guide dog is my own work. The evaluation of ROOin Chapter 3 is based on: V. Dimitrova, R. Denaux, G. Hart, C. Dolbear, I. Holt, and A. G. Cohn, Involving Domain Experts in Authoring OWL Ontologies, in Proceedings of the 7th International Semantic Web Conference, ISWC, 2008, pp. 116. The evaluation discussed in this work was done by me and V. Dimitrova with suppervision by the other authors. G. Hart also contributed to the analysis of the results together with V. Dimitrova. Parts of Chapter 4 were published as: R. Denaux, D. Thakker, V. Dimitrova, and A. G. Cohn, Interactive Semantic Feedback for Intuitive Ontology Authoring, in 7th International Conference on Formal Ontology in Information Systems, 2012. This research was driven by me with guidance from my supervisors. V. Dimitrova and D. Thakker helped to design and perform the evaluation study, while A. G. Cohn supervised the work. This copy has been supplied on the understanding that it is copyright material and that no quotation from the thesis may be published with- out proper acknowledgement. ©2013 University of Leeds and Ronald Denaux to... domain experts, I suppose. Acknowledgements My immediate thanks to both of my supervisors for their valuable comments and nudges in the right direction. Another thanks to them for their dedication, while at the same time giving me the space to go in my own direction. More thanks go to Glen Hart for his trust in me and for supporting the work on ROO. I am also grateful to the other members of the Ordnance Survey {Cathy Dolbear, Ian Holt, John Goodwin, Paula Engelbrecht{ team with whom I collaborated and helped me to get ROO started in the right direction. Thanks to the members of the reading group through the years for keeping things lively and interesting and for providing feedback on my work. Special thanks to Dhaval Thacker for helping out with the Entendre evaluation. Thanks as well to Lora Aroyo, who first brought me in contact with this research area and with Leeds. Finally, also a big thanks to all those who have provided valuable software that I could reuse and build on for my research. Special thanks to Brian Davis and Kaarel Kaljurand for providing their tools. Thanks go, of course, to my parents, brother, close friends and good teachers who have all contributed in one way or another to this thesis being created. A final huge thanks goes to Clare for enduring me during those days before a big deadline and for helping me put research aside once in a while. Abstract Ontologies have been proposed and studied in the last couple of decades as a way to capture and share people's knowledge about the world in a way that is processable by computer systems. Ontologies have the potential to serve as a bridge between the human conceptual understanding of the world and the data produced, processed and stored in computer systems. However, ontologies so far have failed to gather widespread adoption, failing to realise the original vision of the semantic web as a next generation of the world wide web: where everyone would be able to contribute and interlink their data and knowledge as easily as they can contribute and interlink their websites. One of the main reasons for this lack of widespread adoption of ontologies is the steep learning curve for authoring them: most people find it too difficult to learn the syntax and formal semantics of ontology languages. Most research has tried to alleviate this problem by finding ways to help people to collaborate with knowledge engineers when building ontologies; this approach however, requires the wide availability of knowledge engineers, who in practice are scarce. In the context of the semantic web, recent research has started looking at ways to di- rectly capture knowledge from domain experts as ontologies. One such approach advocates the use of Controlled Natural Languages (CNL) as a promising way to alleviate the syntactical impediment to writing ontological constructs. However, not much is yet known about the capabilities and limitations of CNL-based ontol- ogy authoring by domain experts. It is also unknown what type of automatic tool support can and should be provided to novice ontology authors, although such intelligent tool support is becoming possible due to advances in reasoning with existing ontologies and other related areas such as natural language processing. This PhD investigates how CNL-based ontology authoring systems can make ontology authoring more accessible to domain experts by providing intelligent tool support. In particular, this thesis iteratively investigates the impact of pro- viding various types of intelligent tool support for authoring ontologies using the Web Ontology Language (OWL) and a controlled natural language called Rabbit. After each iteration of added tool support, we evaluate how it impacts the ontol- ogy authoring process and what are the main limitations of the resulting ontology authoring system. Based on the found limitations, we decide which further tool support would be most beneficial to novice ontology authors. This methodol- ogy resulted in iteratively providing support for (i) understanding the syntactic capabilities and limitations of the chosen controlled natural language; (ii) fol- lowing appropriate ontology engineering methodologies; (iii) fostering awareness about the logical consequences of adding new knowledge to an ontology and (iv) interacting with the ontology authoring system via dialogues. The main contributions of this PhD are (i) showing that domain experts benefit from guidance about the ontology authoring process and understandable syntax error messages for finding the correct CNL syntax; (ii) the definition of a framework to integrate the syntactical and semantic analyses of ontology authors' inputs; (iii) showing that intuitive feedback about the integration of ontology authors' inputs into an existing ontology benefits ontology authors as they become aware of potential ontology defects; (iv) the definition of a framework to analyse and describe ontology authoring in terms of dialogue moves and their discourse structure. Abbreviations ACE Attempto Controlled English AG Annotation Graph BNF Backus Naur Form cf communicative function CL Controlled Language CNL Controlled Natural Language DE Domain Expert DL Description Logic dm dialogue move fs functional segment fundep functional dependency GUI Graphical User Interface IC Informational Component ISU Information-State-Update KE Knowledge Engineer NL Natural Language NLP Natural Language Processing O Ontology OA Ontology Authoring or Ontology Author OAs Ontology Authors POI Point of Interest POS Part of Speech sc semantic content SW Semantic Web Contents 1 Introduction 1 2 Intuitive Ontology Authoring 6 2.1 Ontology Authoring . .6 2.1.1 Preliminaries . .7 2.1.2 Involving Domain Experts . 10 2.2 CNL-Based Ontology Authoring . 16 2.2.1 CNLs for Knowledge Formulation . 17 2.2.2 Syntactic Support . 22 2.3 Discussion and Open Issues . 23 3 ROO: CNL-Based Ontology Authoring 27 3.1 An Existing Methodology for Involving Domain Experts in Ontol- ogy Authoring . 28 3.1.1 The Rabbit Controlled Natural Language . 29 3.2 ROO: Rabbit to OWL Ontology Authoring Tool . 32 3.2.1 Architectural Overview . 33 3.3 Providing Domain Expert-Specific Tool Support for Rabbit .... 35 3.3.1 RabbitParser . 35 3.3.2 Handling Ambiguity in Rabbit sentences . 39 3.3.3 Support for Editing Rabbit .................. 45 3.3.4 Support for Following Ontology Engineering Methodology 47 3.4 Evaluation . 50 3.4.1 Preliminary User Studies . 50 3.4.2 Experimental Design . 51 9 CONTENTS 3.4.3 Results . 54 3.4.4 Benefits and Limitations of CNL-based Interaction for On- tology Authoring . 63 3.5 Practical Experience with ROO ................... 67 3.6 Conclusion . 70 4 Entendre: Understanding Ontology Authors' Inputs 72 4.1 Analysing Ontology Authors' Inputs . 74 4.2 Approaches to Understanding Ontology Authors .
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