Criteria and Evaluation for Ontology Modularization Techniques
Summary
While many authors have argued for the benefits of applying principles of modularization to ontologies, there is not yet a common understanding of how modules are defined and what properties they should have. In the previous section, this question was addressed from a purely logical point of view. In this chapter, we take a broader view on possible criteria that can be used to determine the quality of a modules. Such criteria include logic-based, but also structural and application-dependent criteria, sometimes borrowing from related fields such as software engineering. We give an overview of possible criteria and identify a lack of application-dependent quality measures. We further report some modularization experiments and discuss the role of quality criteria and evaluation in the context of these experiments.
Highlights
Introduction
Scenarios
- ontology partitioning (a set of modules that form the original)
- selective use and re-use ( a smaller part of an ontology that covers certain aspects of the domain is identified as a basis for a specific application.)
Use Cases for Modularization
- maintenance
- publication (solution-specific subsets)
- validation (experts have to fit the ontology into their brain)
- What is missing is an abstracted view on the overall model and its structure as well as the possibility to focus the inspection of a specific aspect
- processing, aka scalability
Modularization Approaches
Partitioning Approaches
- some approaches being labeled as partitioning methods do not actually create partitions, as the resulting modules may overlap.
Module Extraction Approaches
- traversal approach: starting from the elements of the input sub-vocabulary, relations in the ontology are recursively “traversed” to gather relevant (i.e. related) elements to be included in the module.
- Such a technique has been integrated in the Prompt tool
Evaluation Criteria for Modularization
Logical Criteria
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