Modular Ontology Modeling

Tracking #: 2886-4100

Cogan Shimizu
Karl Hammar
Pascal Hitzler

Responsible editor: 
Guest Editors ESWC 2020

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Full Paper
Reusing ontologies for new purposes, or adapting them to new use-cases, is frequently difficult. In our experiences, we have found this to be the case for several reasons: (i) differing representational granularity in ontologies and in use-cases, (ii) lacking conceptual clarity in potentially reusable ontologies, (iii) lack and difficulty of adherence to good modeling principles, and (iv) a lack of reuse emphasis and process support available in ontology engineering tooling. In order to address these concerns, we have developed the Modular Ontology Modeling (MOMo) methodology, and its supporting tooling infrastructure, CoModIDE (the \textit{Comprehensive Modular Ontology IDE} -- ``commodity''). MOMo builds on the established eXtreme Design methodology, and like it emphasizes modular development and design pattern reuse; but crucially adds the extensive use of graphical schema diagrams, and tooling that support them, as vehicles for knowledge elicitation from experts. In this paper, we present the MOMo workflow in detail, and describe several useful resources for executing it. In particular, we provide a thorough and rigorous evaluation of CoModIDE in its role of supporting the MOMo methodology's graphical modeling paradigm. We find that CoModIDE significantly improves approachability of such a paradigm, and that it displays a high usability.
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Review #1
Anonymous submitted on 23/Nov/2021
Review Comment:

The paper “Modular Ontology Modeling” presents the Modular Ontology Modeling (MOMo) methodology on the one hand (as an abstract process or workflow) and the Comprehensive Modular Ontology IDE (CoModIDE) on the other. CoModIDE is a tool/implementation – realised as a Protégé plugin – that plays a crucial role when fully implementing the MOMo workflow in a concrete ontology development project. The MOMo workflow comprises the following ten steps: 1. Describe use cases and gather possible data sources; 2. Gather competency questions; 3. Identify key notions for the domain to be modelled; 4. Identify existing ontology design patterns to be used; 5. Create schema diagrams for modules; 6. Set up documentation and determine axioms for each module; 7. Create ontology schema diagram from the module schema diagrams; 8. Add axioms spanning more than one module; 9. Reflect on entity naming and all axioms; 10. Create OWL file(s).

This is a review of the revised version of the paper. Many of the remarks from the initial review have been taken into account. Having said that, below I have one final request.

In the final version of the manuscript, the authors should (i) mention the fact that there is no comparable tool available that could be used for benchmarking; (ii) better qualify their use of protege and the goal of the evaluation in the text; and (iii) highlight that although the results are not surprising they speak in favor of pattern aware ontology engineering tooling.