Leveraging Cloud Computing for the Semantic Web - Review and Trends.pdf (451.72 kB)
Leveraging cloud computing for the semantic web: review and trends
journal contribution
posted on 2020-11-29, 00:33 authored by Oluwasegun Adedugbe, Elhadj Benkhelifa, Russell Campion, Feras Al-Obeidat, Anoud Bani Hani, Uchitha JayawickramaUchitha JayawickramaSemantic and cloud computing technologies have become vital elements for developing and deploying solutions across diverse fields in computing. While they are independent of each other, they can be integrated in diverse ways for developing solutions and this has been significantly explored in recent times. With the migration of web-based data and applications to cloud platforms and the evolution of the web itself from a social, web 2.0 to a semantic, web 3.0 comes as the convergence of both technologies. While several concepts and implementations have been provided regarding interactions between the two technologies from existing research, without an explicit classification of the modes of interaction, it can be quite challenging to articulate the interaction modes; hence, building upon them can be a very daunting task. Hence, this research identifies and describes the modes of interaction between them. Furthermore, a “cloud-driven” interaction mode which focuses on fully maximising cloud computing characteristics and benefits for driving the semantic web is described, providing an approach for evolving the semantic web and delivering automated semantic annotation on a large scale to web applications.
Funding
Zayed University (Grant No. RIF)
History
School
- Business and Economics
Department
- Business
Published in
Soft ComputingVolume
24Pages
5999–6014Publisher
SpringerVersion
- AM (Accepted Manuscript)
Rights holder
© Springer-Verlag GmbH Germany, part of Springer Nature 2019Publisher statement
This is a post-peer-review, pre-copyedit version of an article published in Soft Computing. The final authenticated version is available online at: https://doi.org/10.1007/s00500-019-04559-2.Publication date
2019-11-29Copyright date
2020ISSN
1432-7643eISSN
1433-7479Publisher version
Language
- en