3,858 research outputs found
Ontology-based patterns for the integration of business processes and enterprise application architectures
Increasingly, enterprises are using Service-Oriented Architecture (SOA) as an approach to Enterprise Application Integration (EAI). SOA has the potential to bridge
the gap between business and technology and to improve the reuse of existing applications and the interoperability with new ones. In addition to service architecture
descriptions, architecture abstractions like patterns and styles capture design knowledge and allow the reuse of successfully applied designs, thus improving the quality of
software. Knowledge gained from integration projects can be captured to build a repository of semantically enriched, experience-based solutions. Business patterns identify the interaction and structure between users, business processes, and data.
Specific integration and composition patterns at a more technical level address enterprise application integration and capture reliable architecture solutions. We use an
ontology-based approach to capture architecture and process patterns. Ontology techniques for pattern definition, extension and composition are developed and their
applicability in business process-driven application integration is demonstrated
A Semantic-Agent Framework for PaaS Interoperability
Suchismita Hoare, Na Helian, and Nathan Baddoo, 'A Semantic-Agent Framework for PaaS Interoperability', in Proceedings of the The IEEE International Conference on Cloud and Big Data Computing, Toulouse, France, 18-21, July 2016. DOI: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0126 © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Cloud Platform as a Service (PaaS) is poised for a wider adoption by its relevant stakeholders, especially Cloud application developers. Despite this, the service model is still plagued with several adoption inhibitors, one of which is lack of interoperability between proprietary application infrastructure services of public PaaS solutions. Although there is some progress in addressing the general PaaS interoperability issue through various devised solutions focused primarily on API compatibility and platform-agnostic application design models, interoperability specific to differentiated services provided by the existing public PaaS providers and the resultant disparity owing to the offered servicesâ semantics has not been addressed effectively, yet. The literature indicates that this dimension of PaaS interoperability is awaiting evolution in the state-of-the-art. This paper proposes the initial system design of a PaaS interoperability (IntPaaS) framework to be developed through the integration of semantic and agent technologies to enable transparent interoperability between incompatible PaaS services. This will involve uniform description through semantic annotation of PaaS provider services utilizing the OWL-S ontology, creating a knowledgebase that enables software agents to automatically search for suitable services to support Cloud-based Greenfield application development. The rest of the paper discusses the identified research problem along with the proposed solution to address the issue.Submitted Versio
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Enterprise application reuse: Semantic discovery of business grid services
Web services have emerged as a prominent paradigm for the development of distributed software systems as they provide the potential for software to be modularized in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). This paper examines an extension of this paradigm to encompass âGrid Servicesâ, which enables software capabilities to be recast with an operational focus and support a heterogeneous mix of business software and data, termed a Business Grid - "the grid of semantic services". The current industrial representation of services is predominantly syntactic however, lacking the fundamental semantic underpinnings required to fulfill the goals of any semantically-oriented Grid. Consequently, the use of semantic technology in support of business software heterogeneity is investigated as a likely tool to support a diverse and distributed software inventory and user. Service discovery architecture is therefore developed that is (a) distributed in form, (2) supports distributed service knowledge and (3) automatically extends service knowledge (as greater descriptive precision is inferred from the operating application system). This discovery engine is used to execute several real-word scenarios in order to develop and test a framework for engineering such grid service knowledge. The examples presented comprise software components taken from a group of Investment Banking systems. Resulting from the research is a framework for engineering servic
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Ontology learning for Semantic Web Services
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 18/10/2010.The expansion of Semantic Web Services is restricted by traditional ontology engineering methods. Manual ontology development is time consuming, expensive and a resource exhaustive task. Consequently, it is important to support ontology engineers by
automating the ontology acquisition process to help deliver the Semantic Web vision.
Existing Web Services offer an affluent source of domain knowledge for ontology
engineers. Ontology learning can be seen as a plug-in in the Web Service ontology
development process, which can be used by ontology engineers to develop and maintain
an ontology that evolves with current Web Services. Supporting the domain engineer
with an automated tool whilst building an ontological domain model, serves the purpose
of reducing time and effort in acquiring the domain concepts and relations from Web
Service artefacts, whilst effectively speeding up the adoption of Semantic Web Services, thereby allowing current Web Services to accomplish their full potential. With that in mind, a Service Ontology Learning Framework (SOLF) is developed and
applied to a real set of Web Services. The research contributes a rigorous method that
effectively extracts domain concepts, and relations between these concepts, from Web
Services and automatically builds the domain ontology. The method applies pattern-based
information extraction techniques to automatically learn domain concepts and
relations between those concepts. The framework is automated via building a tool that implements the techniques. Applying the SOLF and the tool on different sets of services results in an automatically built domain ontology model that represents semantic knowledge in the underlying domain. The framework effectiveness, in extracting domain concepts and relations, is evaluated
by its appliance on varying sets of commercial Web Services including the financial domain. The standard evaluation metrics, precision and recall, are employed to determine both the accuracy and coverage of the learned ontology models. Both the
lexical and structural dimensions of the models are evaluated thoroughly. The evaluation results are encouraging, providing concrete outcomes in an area that is little researched
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Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL
Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N
Proximal business intelligence on the semantic web
This is the post-print version of this article. The official version can be accessed from the link below - Copyright @ 2010 Springer.Ubiquitous information systems (UBIS) extend current Information System thinking to explicitly differentiate technology between devices and software components with relation to people and process. Adapting business data and management information to support specific user actions in context is an ongoing topic of research. Approaches typically focus on providing mechanisms to
improve specific information access and transcoding but not on how the information
can be accessed in a mobile, dynamic and ad-hoc manner. Although web ontology has been used to facilitate the loading of data warehouses, less research has been carried out on ontology based mobile reporting. This paper explores how business data can be modeled and accessed using the web ontology
language and then re-used to provide the invisibility of pervasive access; uncovering
more effective architectural models for adaptive information system strategies of this type. This exploratory work is guided in part by a vision of business intelligence that is highly distributed, mobile and fluid, adapting to sensory understanding of the underlying environment in which it operates. A proof-of concept mobile and ambient data access architecture is developed in order to further test the viability of such an approach. The paper concludes with an ontology engineering framework for systems of this type â named UBIS-ONTO
A Double Classification of Common Pitfalls in Ontologies
The application of methodologies for building ontologies has improved the ontology quality. However, such a quality is not totally guaranteed because of the difficulties involved in ontology modelling. These difficulties are related to the inclusion of anomalies or worst practices in the modelling. In this context, our aim in this paper is twofold: (1) to provide a catalogue of common worst practices, which we call pitfalls, and (2) to present a double classification of such pitfalls. These two products will serve in the ontology development in two ways: (a) to avoid the appearance of pitfalls in the ontology modelling, and (b) to evaluate and correct ontologies to improve their quality
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