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On Enriching User-Centered Data Integration Schemas in Service Lakes

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Business Information Systems (BIS 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 288))

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Abstract

In the Big Data era, companies are moving away from traditional data-warehouse solutions whereby expensive and time-consuming ETL (Extract-Transform-Load) processes are used, towards data lakes, which can be viewed as storage repositories holding a vast amount of raw data. In this paper, we position ourselves in the recurrent context where a user has a local dataset that is not sufficient for processing the queries that are of interest to him. In this context, we show how the data lake, or more specifically the service lake since we are focusing on data providing services, can be leveraged to enrich the local dataset with concepts that cater for the processing of user queries. Furthermore, we present the algorithms we have developed for this purpose and showcase the working of our solution using a study case.

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Authors and Affiliations

  1. Paris-Dauphine University, PSL Research University, CNRS, [UMR 7243], LAMSADE, 75016, Paris, France

    Hiba Alili, Khalid Belhajjame & Daniela Grigori

  2. National School of Computer Sciences, University of Manouba, RIADI, 2010, Manouba, Tunisia

    Hiba Alili, Rim Drira & Henda Hajjami Ben Ghezala

Authors
  1. Hiba Alili
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  2. Khalid Belhajjame
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  3. Daniela Grigori
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  4. Rim Drira
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  5. Henda Hajjami Ben Ghezala
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Corresponding author

Correspondence to Hiba Alili .

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Editors and Affiliations

  1. Poznan University of Economics, Poznan, Poland

    Witold Abramowicz

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Alili, H., Belhajjame, K., Grigori, D., Drira, R., Ghezala, H.H.B. (2017). On Enriching User-Centered Data Integration Schemas in Service Lakes. In: Abramowicz, W. (eds) Business Information Systems. BIS 2017. Lecture Notes in Business Information Processing, vol 288. Springer, Cham. https://doi.org/10.1007/978-3-319-59336-4_1

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  • DOI: https://doi.org/10.1007/978-3-319-59336-4_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59335-7

  • Online ISBN: 978-3-319-59336-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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