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International Conference on Conceptual Modeling

ER 2019: Advances in Conceptual Modeling pp 213–221Cite as

Framework for Construction and Incremental Maintenance of High-Quality Linked Data Mashup

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11787))

Abstract

Due to the Linked Data initiative, previously isolated datasets are published as linked data. This enables the creation of applications that consume data from multiple Linked Data sources. Applications are confronted with the challenge of obtaining a homogenized view of this global data space, called a Linked Data Mashup view. This work proposes a framework to perform the fusion of Linked Data and quality assessment of Linked Data Mashup. Quality assessment of Linked Data mashup is computed based on the result of the data fusion. We also propose the implementation of a platform for creation and incremental maintenance of mashup views.

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Author information

Authors and Affiliations

  1. Departamento de Computação, Federal University of Ceará, Fortaleza, Ceará, Brazil

    Narciso Arruda

Authors
  1. Narciso Arruda
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Correspondence to Narciso Arruda .

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Editors and Affiliations

  1. Free University of Bozen-Bolzano, Bolzano, Italy

    Giancarlo Guizzardi

  2. Ghent University, Ghent, Belgium

    Frederik Gailly

  3. Federal University of Southern Bahia, Salvador, Brazil

    Rita Suzana Pitangueira Maciel

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Arruda, N. (2019). Framework for Construction and Incremental Maintenance of High-Quality Linked Data Mashup. In: Guizzardi, G., Gailly, F., Suzana Pitangueira Maciel, R. (eds) Advances in Conceptual Modeling. ER 2019. Lecture Notes in Computer Science(), vol 11787. Springer, Cham. https://doi.org/10.1007/978-3-030-34146-6_19

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  • DOI: https://doi.org/10.1007/978-3-030-34146-6_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34145-9

  • Online ISBN: 978-3-030-34146-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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