Towards a Standard for Heterogeneous Ontology Integration and Interoperability (original) (raw)
Related papers
2011
Assistive technology, especially for persons with disabilities, increasingly relies on electronic communication among users, between users and their devices, and among these devices. Making such ICT accessible and inclusive often requires remedial programming, which tends to be costly or even impossible. We, therefore, aim at more interoperable devices, services accessing these devices, and content delivered by these services, at the levels of 1. data and metadata, 2. datamodels and data modelling methods and 3. metamodels as well as a meta ontology language. Even though ontologies are widely being used to enable content interoperability, there is currently no unified framework for ontology interoperability itself. This paper outlines the design considerations underlying OntoIOp (Ontology Integration and Interoperability), a new standardisation activity in ISO/TC 37/SC 3 to become an international standard, which aims at filling this gap.
Describing Interoperability: the OoI Ontology
… on Enterprise Modelling …, 2006
Though ontologies are widely used to solve some specific interoperability problems, there is no specific ontology defining what interoperability actually is, independently from any domain. In this paper, we propose and discuss a first version of such an ontology, namely the OoI (Ontology of Interoperability), which we formalized using the Ontology Web Language (OWL). On the basis of previous research efforts having lead to UML formalization of our model of Interoperability, we use this paper for presenting the OWL version and for linking and comparing it with other models dealing with Interoperability: maturity models for interoperability like e.g. the Levels of Information System Interoperability (LISI) model, and the Model Morphisms ontology (MoMo), which deals with interoperability of models. Finally, we illustrate in a brief use case how the OoI could be used with MoMo to provide solutions to interoperability problems between two models.
Ontologies for Interoperability
Advanced Information and Knowledge Processing, 2011
The goal of this chapter is to help readers understand how ontologies can be used to improve interoperability between heterogeneous information systems. We understand interoperability as the ability of an information system or its components to share information and applications. In the literature there is not a common agreement on which types of interoperability can be found between heterogeneous systems, but mainly classifications of the different types of heterogeneity that can be found between systems and the levels or layers where this heterogeneity has to be solved or overcome. However, this is not the purpose of this chapter. We will focus on which types of system interoperability can be resolved by ontologies, and which types of ontologies have been normally used for this purpose. About ontology types, we refer to the first ontology classification presented in Chap. 1.
Towards semantic interoperability standards based on ontologies
2019
This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No.732240 (SynchroniCity) and No. 688467 (VICINITY); from ETSI under Specialist Task Forces 534, 556, and 566. This work is partially funded by Hazards SEES NSF Award EAR 1520870, and KHealth NIH 1 R01 HD087132-01.
Tools and Techniques for Ontology Interoperability: A Survey
The idea of the semantic web is to add machine process able information to web-based data in order to realize interoperability. Ontology is a shared conceptualization of knowledge representation of particular domain. These are used for the enhancement of semantic information explicitly. Ontologies play a prominent role in the concept of the semantic web to provide semantic information for assisting communication among heterogeneous information repositories. Ontology Interoperability provides the reusability of ontologies Different domain experts and ontology engineers create different ontologies for the same or similar domain depending on their data modeling requirements. These cause ontology heterogeneity and inconsistency problems. As increasing numbers of ontologies are developed by diverse communities, the demand for rapid ontology mapping is arising. For more better and precise results ontology mapping is the solution. As their use has increased, providing means of resolving semantic differences has also become very important. Papers on ontology interoperability report the results on different frameworks and this makes their comparison almost impossible. Therefore, the main focus of this paper will be on providing some basics of ontology interoperability and briefly introducing its different approaches. In this paper we survey the approaches that have been proposed for providing interoperability among domain ontologies and its related techniques and tools. https://sites.google.com/site/ijcsis/
Will my Ontologies Fit Together? Technical Report
In realistic applications, it is often desirable to integrate different ontologies 1 into a single, reconciled ontology. Ideally, one would expect the individual ontologies to be developed as independently as possible from the rest, and the final reconciliation to be seamless and free from unexpected results. This would allow for the modular design of large ontologies and would facilitate knowledge reuse tasks. Few ontology development tools, however, provide any support for integration, and there has been relatively little study of the problem at a fundamental level.
The role of ontologies in enabling dynamic interoperability
2011
Advances in the middleware paradigm has enabled applications to be integrated together thus enabling more reliable distributed systems. Although every middleware tries to solve interoperability issues among a given set of applications, nonetheless there still remains interoperability challenges across various middlewares. Interoperability enables diverse systems to work in accordance and extend the scope of services that are provided by individual systems.
The purpose of this document is to identify requirements that are too general to result from any single use case area, cut across all use cases areas, or are not directly related to the existing use cases, but nonetheless important. ... The following requirements are recommended by the group. ... Ontologies are publicly available and different data sources can commit to the same ontology for shared meaning. ... Any use case in which distributed data sources use shared terminology. ... Interoperability requires agreements on the definitions of terms. ...
OCEAN: an ontology for supporting interoperability service utilities in virtual organisations
International Journal of Networking and Virtual Organisations, 2011
Semantic interoperability is a crucial issue in industrial enterprises when they participate in virtual organisations (VOs), i.e., when they dynamically form network-based collaborative alliances of a temporary nature. Addressing semantic heterogeneities aims to ensure that the meaning of information exchanged by VOs is interpreted in the same way by all communicating parties and their systems. In this paper we examine how ontologies can be employed by a system of services for delivering interoperability to enterprises, independent of particular IT deployments. In order to support interoperability service utilities in VOs, this paper presents a top-level ontology for collaborative networked organisations (code named OCEAN). The OCEAN ontology is designed as a lightweight top-level ontology that provides a common terminological reference in terms of VOs. The paper also demonstrates the use of practical tools for achieving consensus of the shared conceptualisation of a virtual organisation (VO), among participants, while it outlines a service-oriented architecture (SOA) for supporting VO knowledge based collaborations using OCEAN. We demonstrate how that usage enables shared understanding in knowledge-intensive collaborations, as well as how it facilitates interoperability of applications that provide collaboration services, presenting concrete examples from the pharmaceutical industry.