Paper Info
Title
Oam: An Ontology Application Management Framework For Simplifying Ontology-Based Semantic Web Application Development
Abstract
Although the Semantic Web data standards are established, ontology-based applications built on the standards are relatively limited. This is partly due to high learning curve and efforts demanded in building ontology-based Semantic Web applications. In this paper, we describe an ontology application management (OAM) framework that aims to simplify creation and adoption of ontology-based application that is based on the Semantic Web technology. OAM introduces an intermediate layer between user application and programming and development environment in order to support ontology-based data publishing and access, abstraction and interoperability. The framework focuses on providing reusable and configurable data and application templates, which allow the users to create the applications without programming skill required. Three forms of templates are introduced: database to ontology mapping configuration, recommendation rule and application templates. We describe two case studies that adopted the framework: activity recognition in smart home domain and thalassemia clinical support system, and how the framework was used in simplifying development in both projects. In addition, we provide some performance evaluation results to show that, by limiting expressiveness of the rule language, a specialized form of recommendation processor can be developed for more efficient performance. Some advantages and limitations of the application framework in ontology-based applications are also discussed.
Year
DOI
Venue
2016
10.1142/S0218194016500066
INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING
Keywords
Field
DocType
Semantic Web application framework, ontology application framework, ontologybased data publishing and access, knowledge-based application development tools
Ontology (information science),Ontology alignment,Data mining,Ontology-based data integration,Process ontology,Computer science,Ontology Inference Layer,OWL-S,Suggested Upper Merged Ontology,Upper ontology
Journal
Volume
Issue
ISSN
26
1
0218-1940
Citations 
PageRank 
References 
3
0.48
22
Authors
9
Name
Order
Citations
PageRank
Marut Buranarach16311.74
Thepchai Supnithi214129.40
Ye Myat Thein3172.39
Taneth Ruangrajitpakorn4118.53
Thanyalak Rattanasawad550.86
Konlakorn Wongpatikaseree6283.21
Azman Osman Lim76712.26
Yasuo Tan84920.68
Anunchai Assawamakin9956.16