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From Data Integration to Big Data Integration

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A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years

Part of the book series: Studies in Big Data ((SBD,volume 31))

Abstract

The Database Group (DBGroup, www.dbgroup.unimore.it) and Information System Group (ISGroup, www.isgroup.unimore.it) research activities have been mainly devoted to the Data Integration Reserach Area. The DBGroup designed and developed the MOMIS data integration system, giving raise to a successful innovative enterprise DataRiver (www.datariver.it), distributing MOMIS as open source. MOMIS provides an integrated access to structured and semistructured data sources and allows a user to pose a single query and to receive a single unified answer. Description Logics, Automatic Annotation of schemata plus clustering techniques constitute the theoretical framework. In the context of data integration, the ISGroup addressed problems related to the management and querying of heterogeneous data sources in large-scale and dynamic scenarios. The reference architectures are the Peer Data Management Systems and its evolutions toward dataspaces. In these contexts, the ISGroup proposed and evaluated effective and efficient mechanisms for network creation with limited information loss and solutions for mapping management query reformulation and processing and query routing. The main issues of data integration have been faced: automatic annotation, mapping discovery, global query processing, provenance, multidimensional Information integration, keyword search, within European and national projects. With the incoming new requirements of integrating open linked data, textual and multimedia data in a big data scenario, the research has been devoted to the Big Data Integration Research Area. In particular, the most relevant achieved research results are: a scalable entity resolution method, a scalable join operator and a tool, LODEX, for automatically extracting metadata from Linked Open Data (LOD) resources and for visual querying formulation on LOD resources. Moreover, in collaboration with DATARIVER, Data Integration was successfully applied to smart e-health.

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Notes

  1. 1.

    NORMS will be included in the next release of the MOMIS Open Source version, available at http://www.datariver.it/data-integration/momis/.

  2. 2.

    http://www.tpc.org/tpch.

  3. 3.

    For a complete description see http://dbgroup.ing.unimore.it/MomisDashboard.

  4. 4.

    http://stravanni.github.io/blast/.

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Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria Enzo Ferrari, Università di Modena e Reggio Emilia, Modena, Italy

    Sonia Bergamaschi, Domenico Beneventano, Francesco Guerra, Laura Po, Maurizio Vincini & Giovanni Simonini

  2. Datariver s.r.l., Modena, Italy

    Mirko Orsini & Luca Magnotta

  3. FIM, Università di Modena e Reggio, Modena, Italy

    Federica Mandreoli & Riccardo Martoglia

  4. ICT School, Università di Modena e Reggio, Modena, Italy

    Song Zhu, Luca Gagliardelli & Luca Magnotta

Authors
  1. Sonia Bergamaschi
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  2. Domenico Beneventano
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  3. Federica Mandreoli
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  4. Riccardo Martoglia
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  5. Francesco Guerra
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  6. Mirko Orsini
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  7. Laura Po
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  8. Maurizio Vincini
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  9. Giovanni Simonini
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  10. Song Zhu
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  11. Luca Gagliardelli
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  12. Luca Magnotta
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Corresponding author

Correspondence to Sonia Bergamaschi .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Sergio Flesca

  2. University of Calabria, Rende, Italy

    Sergio Greco

  3. ICAR-CNR, Rende, Italy

    Elio Masciari

  4. University of Calabria, Rende, Italy

    Domenico Saccà

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Bergamaschi, S. et al. (2018). From Data Integration to Big Data Integration. In: Flesca, S., Greco, S., Masciari, E., Saccà, D. (eds) A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years. Studies in Big Data, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-319-61893-7_3

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  • DOI: https://doi.org/10.1007/978-3-319-61893-7_3

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