Change management in evolving web ontologies

Khattak, Asad Masood; Latif, Khalid; Lee, Sungyoung

doi:10.1016/j.knosys.2012.05.005

Cited by 40 publications

(30 citation statements)

References 23 publications

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“…To maintain the coherence of an ontology during its evolution, the authors of [11][12][13] have proposed a posteriori approaches. This type of approach allows the application of changes in order to evaluate the evolution impact on the ontology, then suggests how to repair inconsistencies in case of problems.…”

Section: Related Workmentioning

confidence: 99%

“…During this project, ontology engineers had to manage naRyQ changes. Based on the methodological guidelines given in [1], we propose the workflow given in Figure 1 for carrying out the ontology evolution activity, then we combined, adapted and extended existing approaches in ontology evolution [8][9][10][11][12][13], and finally we implemented a plug-in, called DynarOnto, to fit naRyQ evolution needs. Our paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

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Ontology Evolution for Experimental Data in Food

Touhami

Buche

Dibie-Barthelemy

et al. 2015

Communications in Computer and Information Science

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Abstract. Throughout its life cycle, an ontology may change in order to adapt to domain changes or to new usages. This paper presents an ontology evolution activity [1] applied to an ontology dedicated to the annotation of experimental data in food [2], and a plug-in, DynarOnto, which assists ontology engineers for carrying out the ontology changes. Our evolution method is an a priori method which takes as input an ontology in a consistent state, implements the changes selected to be applied and manages all the consequences of those changes by producing an ontology in a consistent state.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ontology Evolution for Experimental Data in Food

Touhami

Buche

Dibie-Barthelemy

et al. 2015

Communications in Computer and Information Science

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“…Some of the important frameworks are CONCORDIA ( [6]), CHAO ( [7]), Evolva ( [8], [9]), GOMMA ( [10]), COnto-Diff ( [11]) and CHO (Change History Ontology) ( [12], [13], [14]). However, only a few of the frameworks address the change propagation phase, such as [2], [6], [7], [15], [16] and [17].…”

Section: Related Workmentioning

confidence: 99%

Ontology-based Change Propagation in Shareable Health Information Applications

Sari¹,

Rahayu²

2015

ijacsa

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Abstract-One of the most important challenges to be addressed when establishing an integrated smart health environment is the availability of shareable health data and knowledge which standardize the interoperability of components within the environment. Health ontologies are commonly utilized to enable interoperability between applications in such environment. However, the dynamic nature of health knowledge causes the need for frequent changes in health ontologies which then must be propagated to the relevant applications. A change propagation method that can efficiently streamline the change management from an ontology to all the applications which reference to it is proposed. A component called a mapper is used to manage the mapping between application terms and ontology concepts. The mapper is aimed to maintain the applications' access to the most up-to-date ontology concepts and to improve the semantic mapping between the application terms and the ontology concepts. Some rules are developed for the change propagation process. The evaluation of the method shows that the mapper can improve the mapping list in terms of: (i) correctness, by proposing a new mapping entry to substitute an existing one which is not valid anymore because ontology concept is deleted or changed; (ii) currency maintenance, by recommending a better mapping between an application term and a new ontology concept based on the similarity value between the term and the new concept.

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“…It is essential for sharing information among independent organizations, and exchange information among heterogeneous applications of Information Systems. To make this possible, we need to model the domain knowledge while preserving its semantics [3]. The development of ontologies is becoming a crucial part of semantic web and knowledge management in the organizations.…”

Section: Introductionmentioning

confidence: 99%

“…Support for change management is vital to support distributed ontologies. Preserving consistency, while accommodating new changes, is a crucial task that needs special attention [3]. Also, matching between ontologies are easily affected by changes in the ontologies because a change in one ontology could effects the others.…”

Section: Introductionmentioning

confidence: 99%

Towards Ontology Lifecycle: Building, Matching and Evolution to Semantically Integrate Application Ontologies

Razika¹

2017

IJCATR

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Semantic interoperability among applications, systems, and services are mostly based on ontology. Its increase usage in Information Systems and knowledge sharing systems raises the importance of ontology development and maintenance. It is essential for sharing information among independent organizations, exchange of information among heterogeneous systems. To make this possible, we need to carefully model the domain knowledge while preserving its semantics. Ontologies are complex in nature and often structured. Their development and maintenance incorporate research areas like: building, evolution, versioning, matching and integration where these are fundamentally different. We uncover the gap in the current research area of ontology building, matching and evolution. We propose a research direction based on ontology construction using knowledge extraction, matching evolution between versions. This paper presents system architecture to manage the lifecycle of the application ontology incorporating building, matching and evolution processes. This solution is integrated in the source ontology since its creation in order to make it possible to evolve and to be versioned.

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Change management in evolving web ontologies

Cited by 40 publications

References 23 publications

Ontology Evolution for Experimental Data in Food

Ontology Evolution for Experimental Data in Food

Ontology-based Change Propagation in Shareable Health Information Applications

Towards Ontology Lifecycle: Building, Matching and Evolution to Semantically Integrate Application Ontologies

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