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FedSDM: Semantic Data Manager for Federations of RDF Datasets

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Data Integration in the Life Sciences (DILS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 11371))

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Abstract

Linked open data movements have been followed successfully in different domains; thus, the number of publicly available RDF datasets and linked data based applications have increased considerably during the last decade. Particularly in Life Sciences, RDF datasets are utilized to represent diverse concepts, e.g., proteins, genes, mutations, diseases, drugs, and side effects. Albeit publicly accessible, the exploration of these RDF datasets requires the understanding of their main characteristics, e.g., their vocabularies and the connections among them. To tackle these issues, we present and demonstrate FedSDM, a semantic data manager for federations of RDF datasets. Attendees will be able to explore the relationships among the RDF datasets in a federation, as well as the characteristics of the RDF classes included in each RDF dataset (https://github.com/SDM-TIB/FedSDM).

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Notes

  1. 1.

    https://networkx.github.io/.

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Acknowledgements

This work has been funded by the EU H2020 RIA under the Marie Skłodowska-Curie grant agreement No. 642795 (WDAqua) and EU H2020 Programme for the projects with GA No. 727658 (IASIS).

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Authors and Affiliations

  1. L3S Research Center, Hannover, Germany

    Kemele M. Endris, Maria-Esther Vidal & Sören Auer

  2. TIB Leibniz Information Centre for Science and Technology, Hannover, Germany

    Kemele M. Endris, Maria-Esther Vidal & Sören Auer

Authors
  1. Kemele M. Endris
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  2. Maria-Esther Vidal
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  3. Sören Auer
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Corresponding author

Correspondence to Kemele M. Endris .

Editor information

Editors and Affiliations

  1. TIB and Leibniz University, Hannover, Germany

    Sören Auer

  2. TIB and Leibniz University, Hannover, Germany

    Maria-Esther Vidal

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Endris, K.M., Vidal, ME., Auer, S. (2019). FedSDM: Semantic Data Manager for Federations of RDF Datasets. In: Auer, S., Vidal, ME. (eds) Data Integration in the Life Sciences. DILS 2018. Lecture Notes in Computer Science(), vol 11371. Springer, Cham. https://doi.org/10.1007/978-3-030-06016-9_8

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  • DOI: https://doi.org/10.1007/978-3-030-06016-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-06015-2

  • Online ISBN: 978-3-030-06016-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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