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Semantic Data Integration

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Handbook of Big Data Technologies

Abstract

The growing volume, variety and complexity of data being collected for scientific purposes presents challenges for data integration. For data to be truly useful, scientists need not only to be able to access it, but also be able to interpret and use it. Doing this requires semantic context. Semantic Data Integration is an active field of research, and this chapter describes the current challenges and how existing approaches are addressing them. The chapter then provides an overview of several active research areas within the semantic data integration field, including interactive and collaborative schema matching, integration of geospatial and biomedical data, and visualization of the data integration process. Finally, the need to move beyond the discovery of simple 1-to-1 equivalence matches to the identification of more complex relationships across datasets is presented and possible first steps in this direction are discussed.

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Notes

  1. 1.

    http://www.w3.org/DesignIssues/LinkedData.html.

  2. 2.

    http://mapekus.fiit.stuba.sk.

  3. 3.

    http://oaei.ontologymatching.org.

  4. 4.

    http://oaei.ontologymatching.org/2013/interactive/index.html.

  5. 5.

    www.geonames.org.

  6. 6.

    http://linkedgeodata.org.

  7. 7.

    http://data.ordnancesurvey.co.uk.

  8. 8.

    http://www.opengeospatial.org/standards/gml.

  9. 9.

    http://www.opengeospatial.org/standards/geosparql.

  10. 10.

    http://www.opengeospatial.org/standards/kml.

  11. 11.

    http://www.opengeospatial.org/standards/wfs.

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Acknowledgements

This work was supported in part by the National Science Foundation award 1440202 GeoLink - Leveraging Semantics and Linked Data for Data Sharing and Discovery in the Geosciences. It was also partially supported by Fundaç ão para a Ciência e Tecnologia (PTDC/EEI-ESS/4633/2014).

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Authors and Affiliations

  1. DaSe Laboratory, Wright State University, Dayton, OH, USA

    Michelle Cheatham

  2. Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

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  1. Michelle Cheatham
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  2. Catia Pesquita
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Correspondence to Michelle Cheatham .

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  1. School of Information Technologies, The University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

  2. The School of Computer Science, The University of New South Wales, Eveleigh, New South Wales, Australia

    Sherif Sakr

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Cheatham, M., Pesquita, C. (2017). Semantic Data Integration. In: Zomaya, A., Sakr, S. (eds) Handbook of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-49340-4_8

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