Semantically-enriched and semi-Autonomous collaboration framework for the Web of Things. Design, implementation and evaluation of a multi-party collaboration framework with semantic annotation and representation of sensors in the Web of Things and a case study on disaster management
KeywordSemantic Web; Web of Things; Multi-party Collaboration Framework; Semantic annotation; Semantic Sensor Network ontology (SSN); Cloud computing; Service-oriented Architecture (SoA); Resource-based data model; Resource-oriented access control; Disaster management
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentFaculty of Engineering & Informatics
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AbstractThis thesis proposes a collaboration framework for the Web of Things based on the concepts of Service-oriented Architecture and integrated with semantic web technologies to offer new possibilities in terms of efficient asset management during operations requiring multi-actor collaboration. The motivation for the project comes from the rise in disasters where effective cross-organisation collaboration can increase the efficiency of critical information dissemination. Organisational boundaries of participants as well as their IT capability and trust issues hinders the deployment of a multi-party collaboration framework, thereby preventing timely dissemination of critical data. In order to tackle some of these issues, this thesis proposes a new collaboration framework consisting of a resource-based data model, resource-oriented access control mechanism and semantic technologies utilising the Semantic Sensor Network Ontology that can be used simultaneously by multiple actors without impacting each other’s networks and thus increase the efficiency of disaster management and relief operations. The generic design of the framework enables future extensions, thus enabling its exploitation across many application domains. The performance of the framework is evaluated in two areas: the capability of the access control mechanism to scale with increasing number of devices, and the capability of the semantic annotation process to increase in efficiency as more information is provided. The results demonstrate that the proposed framework is fit for purpose.
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A note on intelligent exploration of semantic dataThakker, Dhaval; Schwabe, D.; Garcia, D.; Kozaki, K.; Brambilla, M.; Dimitrova, V. (2019-04)Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles three technical contributions that significantly advance the state-of-the-art in exploration of semantic data using semantic web techniques and technologies.
A generic and extensible asset model for a semantic collaboration frameworkAmir, Mohammad; Hu, Yim Fun; Pillai, Prashant (2014-02-25)Analysis of existing literature reveals the growing need to tackle the issue of unified data dissemination. Where this issue has been given some focus, the outreach has been more or less limited to similar systems (i.e. cross-instance collaboration) and no particular focus has been applied on the problem of exposing this data or knowledge to third parties (i.e. cross-vendor collaboration). This paper proposes an integration of semantic technologies within the Web of Things based on the concept and principles of the Service-Oriented Architecture to realize a distributed and semi-autonomous collaboration framework that is capable of offering cross-vendor information exchange and collaboration facilities. Powered by a semantic engine and exposed as a web application with a RESTful API, the generic framework realizes an extensible knowledge management and exchange system that accounts for the dynamic landscape in business-centric Web of Things applications. Disaster management is taken as a potential application scenario to critically analyse and evaluate the system prototype and show that the asset model for the proposed framework is sufficiently capable of meeting the modern-day and next-generation collaboration needs in a world of ever-increasing cross-vendor information sharing.
Analytics-as-a-Service in a Multi-Cloud Environment through Semantically-enabled Hierarchical Data ProcessingJayaraman, P.P.; Perera, C.; Georgakopoulos, D.; Dustdar, S.; Thakker, Dhaval; Ranjan, R. (2017-08)A large number of cloud middleware platforms and tools are deployed to support a variety of Internet of Things (IoT) data analytics tasks. It is a common practice that such cloud platforms are only used by its owners to achieve their primary and predefined objectives, where raw and processed data are only consumed by them. However, allowing third parties to access processed data to achieve their own objectives significantly increases intergation, cooperation, and can also lead to innovative use of the data. Multicloud, privacy-aware environments facilitate such data access, allowing different parties to share processed data to reduce computation resource consumption collectively. However, there are interoperability issues in such environments that involve heterogeneous data and analytics-as-a-service providers. There is a lack of both - architectural blueprints that can support such diverse, multi-cloud environments, and corresponding empirical studies that show feasibility of such architectures. In this paper, we have outlined an innovative hierarchical data processing architecture that utilises semantics at all the levels of IoT stack in multicloud environments. We demonstrate the feasibility of such architecture by building a system based on this architecture using OpenIoT as a middleware, and Google Cloud and Microsoft Azure as cloud environments. The evaluation shows that the system is scalable and has no significant limitations or overheads.