Get my pizza right: Repairing missing is-a relations in ALC ontologies (extended version)

With the increased use of ontologies in semantically-enabled applications, the issue of debugging defects in ontologies has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Debugging consists of the phases of detection and repairing. In this paper we focus on the repairing phase of a particular kind of defects, i.e. the missing relations in the is-a hierarchy. Previous work has dealt with the case of taxonomies. In this work we extend the scope to deal with ALC ontologies that can be represented using acyclic terminologies. We present algorithms and discuss a system

CONGAS: a collaborative ontology development framework based on Named GrAphS

The process of ontology development involves a range of skills and know-how often requiring team work of different people, each of them with his own way of contributing to the definition and formalization of the domain representation. For this reason, collaborative development is an important feature for ontology editing tools, and should take into account the different characteristics of team participants, provide them with a dedicated working environment allowing to express their ideas and creativity, still protecting integrity of the shared work. In this paper we present CONGAS, a collaborative version of the Knowledge Management and Acquisition platform Semantic Turkey which, exploiting the potentialities brought by recent introduction of context management into RDF triple graphs, offers a collaborative environment where proposals for ontology evolution can emerge and coexist, be evaluated by team users, trusted across different perspectives and eventually converged into the main development stream

Generation and matching of ontology data for the semantic web in a peer-to-peer framework

The abundance of ontology data is very crucial to the emerging semantic web. This paper proposes a framework that supports the generation of ontology data in a peer-to-peer environment. It not only enables users to convert existing structured data to ontology data aligned with given ontology schemas, but also allows them to publish new ontology data with ease. Besides ontology data generation, the common issue of data overlapping over the peers is addressed by the process of ontology data matching in the framework. This process helps turn the implicitly related data among the peers caused by overlapping into explicitly interlinked ontology data, which increases the overall quality of the ontology data. To improve matching accuracy, we explore ontology related features in the matching process. Experiments show that adding these features achieves better overall performance than using traditional features only. © Springer-Verlag Berlin Heidelberg 2007

Нарушения в геноме хозяина при экспериментальном гименолепидозе в зависимости от дозы введенного инвазивного материала при заряжении

ГИМЕНОЛЕПИДО

Towards Ontology Evolution in Physics

Abstract. We investigate the problem of automatically repairing incon-sistent ontologies. A repair is triggered when a contradiction is detected between the current theory and new experimental evidence. We are work-ing in the domain of physics because it has good historical records of such contradictions and how they were resolved. We use these records to both develop and evaluate our techniques. To deal with problems of inferential search control and ambiguity in the atomic repair operations, we have developed ontology repair plans, which represent common patterns of re-pair. They first diagnose the inconsistency and then direct the resulting repair. Two such plans have been developed to repair ontologies that dis-agree over the value and the dependence of a function, respectively. We have implemented the repair plans in the galileo system and success-fully evaluated galileo on a diverse range of examples from the history of physics.

Dependencies between modularity metrics towards improved modules

Recent years have seen many advances in ontology modularisation. This has made it difficult to determine whether a module is actually a good module; it is unclear which metrics should be considered. The few existing works on evaluation metrics focus on only some metrics that suit the modularisation technique, and there is not always a quantitative approach to calculate them. Overall, the metrics are not comprehensive enough to apply to a variety of modules and it is unclear which metrics fare well with particular types of ontology modules. To address this, we create a comprehensive list of module evaluation metrics with quantitative measures. These measures were implemented in the new Tool for Ontology Module Metrics (TOMM) which was then used in a testbed to test these metrics with existing modules. The results obtained, in turn, uncovered which metrics fare well with which module types, i.e., which metrics need to be measured to determine whether a module of some type is a ‘good’ module

Controlled English for Reasoning on the Semantic Web

The existing Semantic Web languages have a very technical focus and fail to provide good usability for users with no background in formal methods. We argue that controlled natural languages like Attempto Controlled English (ACE) can solve this problem. ACE is a subset of English that can be translated into various logic based languages, among them the Semantic Web standards OWL and SWRL. ACE is accompanied by a set of tools, namely the parser APE, the Attempto Reasoner RACE, the ACE View ontology and rule editor, the semantic wiki AceWiki, and the Protune policy framework. The applications cover a wide range of Semantic Web scenarios, which shows how broadly ACE can be applied. We conclude that controlled natural languages can make the Semantic Web better understandable and more usable

Reuse of terminological resources for efficient ontological engineering in Life Sciences

This paper is intended to explore how to use terminological resources for ontology engineering. Nowadays there are several biomedical ontologies describing overlapping domains, but there is not a clear correspondence between the concepts that are supposed to be equivalent or just similar. These resources are quite precious but their integration and further development are expensive. Terminologies may support the ontological development in several stages of the lifecycle of the ontology; e.g. ontology integration. In this paper we investigate the use of terminological resources during the ontology lifecycle. We claim that the proper creation and use of a shared thesaurus is a cornerstone for the successful application of the Semantic Web technology within life sciences. Moreover, we have applied our approach to a real scenario, the Health-e-Child (HeC) project, and we have evaluated the impact of filtering and re-organizing several resources. As a result, we have created a reference thesaurus for this project, named HeCTh