Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance

Increasingly, organizations are adopting ontologies to describe their large catalogues of items. These ontologies need to evolve regularly in response to changes in the domain and the emergence of new requirements. An important step of this process is the selection of candidate concepts to include in the new version of the ontology. This operation needs to take into account a variety of factors and in particular reconcile user requirements and application performance. Current ontology evolution methods focus either on ranking concepts according to their relevance or on preserving compatibility with existing applications. However, they do not take in consideration the impact of the ontology evolution process on the performance of computational tasks – e.g., in this work we focus on instance tagging, similarity computation, generation of recommendations, and data clustering. In this paper, we propose the Pragmatic Ontology Evolution (POE) framework, a novel approach for selecting from a group of candidates a set of concepts able to produce a new version of a given ontology that i) is consistent with the a set of user requirements (e.g., max number of concepts in the ontology), ii) is parametrised with respect to a number of dimensions (e.g., topological considerations), and iii) effectively supports relevant computational tasks. Our approach also supports users in navigating the space of possible solutions by showing how certain choices, such as limiting the number of concepts or privileging trendy concepts rather than historical ones, would reflect on the application performance. An evaluation of POE on the real-world scenario of the evolving Springer Nature taxonomy for editorial classification yielded excellent results, demonstrating a significant improvement over alternative approaches

A Versioning Management Model for Ontology-Based Data Warehouses

Abstract. More and more integration systems use ontologies to solve the problem of semantic heterogeneities between autonomous databases. To automate the integration process, a number of these systems suppose the existence of a shared domain ontology a priori referenced by the local ontologies embedded in the various sources. When the shared ontology evolves over the time, the evolution may concern (i) the ontology level, (2) the local schema level, and/or (3) the contents of sources. Since sources are autonomous and may evolve independently, managing the evolution of the integrated system turns to an asynchronous versioning problem. In this paper, we propose an approach and a model to deal with this problem in the context of a materialized integration system. To manage the changes of contents and schemas of sources, we adapt the existing solutions proposed in traditional databases. To support ontology changes, we propose the principle of ontological continuity. It supposes that an evolution of an ontology should not make false an axiom that was previously true. This principle allows the management of each old instance using the new version of ontology. With this assumption, we propose an approach, called the floating version model, that fully automate the whole integration process. Our work is motivated by the automatic integration of catalogs of industrial components in engineering databases. It has been validated by a prototype using ECCO environment and the EXPRESS language.