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Enhancing Workspace Composition by Exploiting Linked Open Data as a Polymorphic Data Source

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 40))

Abstract

In the last decade, the World Wide Web has been evolving as a data infrastructure, where a wide variety of resources is increasingly being made available as Web services. This trend is pushing the researchers to investigate approaches like composition platforms, aimed at empowering end users to access, compose and use these services. Despite the wide availability of data sources, due to the specific and diverse end users’ information needs often no data source can satisfy these needs. This limits the adoption of composition platforms in real contexts and everyday use. In order to overcome this limitation, this paper presents a polymorphic data source that exploits the wide availability of information structured in the Linked Open Data cloud. To build this data source, a semi-automatic annotation algorithm is presented that creates semantic annotations for services available in a composition platform. An implementation of this approach in a mashup platform is described.

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Acknowledgments

This work is partially supported by the Italian Ministry of University and Research (MIUR) under grant PON 02_00563_3470993 “VINCENTE” and by the Italian Ministry of Economic Development (MISE) under grant PON Industria 2015 MI01_00294 “LOGIN”. We also thank the student Vincenzo Lucente for contributing to system implementation.

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Correspondence to Giuseppe Desolda .

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Desolda, G. (2015). Enhancing Workspace Composition by Exploiting Linked Open Data as a Polymorphic Data Source. In: Damiani, E., Howlett, R., Jain, L., Gallo, L., De Pietro, G. (eds) Intelligent Interactive Multimedia Systems and Services. Smart Innovation, Systems and Technologies, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-19830-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-19830-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19829-3

  • Online ISBN: 978-3-319-19830-9

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