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Linked Data Mashups: A Review on Technologies, Applications and Challenges

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Intelligent Information and Database Systems (ACIIDS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8398))

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Abstract

To remedy the data integration issues of the traditional Web mashups, the Semantic Web technology uses the Linked Data based on RDF data model as the unified data model for combining, aggregating and transforms data from heterogeneous data resources to build Linked Data Mashups. There have been tremendous amount of efforts of Semantic Web community to enable Linked Data Mashups but there still lack of a systematic survey on concepts, technologies, applications and challenges. Therefore, this paper gives an overview of Linked Data Mashups and conducts a state-of-the-art survey about technologies, applications and challenges on Linked Data Mashups.

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Author information

Authors and Affiliations

  1. Hue University, 3 Le Loi Street, Hue City, Vietnam

    Tuan Nhat Tran, Duy Khanh Truong, Hanh Huu Hoang & Thanh Manh Le

Authors
  1. Tuan Nhat Tran
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  2. Duy Khanh Truong
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  3. Hanh Huu Hoang
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  4. Thanh Manh Le
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Editor information

Editors and Affiliations

  1. Institute of Informatics, Wrocław University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Ngoc Thanh Nguyen  & Bogdan Trawiński  & 

  2. Faculty of Engineering, Department of Computer Engineering, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Boonwat Attachoo

  3. Software Engineering Program, King Mongkut’s Institute of Technology Ladkrabang, 10520, Bangkok, Thailand

    Kulwadee Somboonviwat

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© 2014 Springer International Publishing Switzerland

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Tran, T.N., Truong, D.K., Hoang, H.H., Le, T.M. (2014). Linked Data Mashups: A Review on Technologies, Applications and Challenges. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8398. Springer, Cham. https://doi.org/10.1007/978-3-319-05458-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-05458-2_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05457-5

  • Online ISBN: 978-3-319-05458-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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