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Data Analysis, Machine Learning and Knowledge Discovery pp 455–462Cite as

Data Enrichment in Discovery Systems Using Linked Data

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Abstract

The Linked Data Web is an abundant source for information that can be used to enrich information retrieval results. This can be helpful in many different scenarios, for example to enable extensive multilingual semantic search or to provide additional information to the users. In general, there are two different ways to enrich data: client-side and server-side. With client-side data enrichment, for instance by means of JavaScript in the browser, users can get additional information related to the results they are provided with. This additional information is not stored within the retrieval system and thus not available to improve the actual search. An example is the provision of links to external sources like Wikipedia, merely for convenience. By contrast, an enrichment on the server-side can be exploited to improve the retrieval directly, at the cost of data duplication and additional efforts to keep the data up-to-date. In this paper, we describe the basic concepts of data enrichment in discovery systems and compare advantages and disadvantages of both variants. Additionally, we introduce a JavaScript Plugin API that abstracts from the underlying system and facilitates platform independent client-side enrichments.

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Notes

  1. 1.

    http://www.exlibrisgroup.com/category/PrimoOverview/.

  2. 2.

    http://www.exlibrisgroup.com/category/PrimoCentral.

  3. 3.

    http://www.serialssolutions.com/en/services/summon/.

  4. 4.

    As RECID, the record ID of Primo is used. For example: MAN_ALEPH00143741.

  5. 5.

    Gemeinsame Normdatei. Authority file provided by the German National Library.

  6. 6.

    http://dbpedia.org.

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Acknowledgements

We like to thank Bernd Fallert for his great work on the implementation.

Author information

Authors and Affiliations

  1. Mannheim University Library, Mannheim, Germany

    Dominique Ritze

  2. University of Mannheim, Mannheim, Germany

    Kai Eckert

Authors
  1. Dominique Ritze
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  2. Kai Eckert
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Corresponding author

Correspondence to Dominique Ritze .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Myra Spiliopoulou

  2. Institute of Computer Science, University of Hildesheim, Hildesheim, Germany

    Lars Schmidt-Thieme

  3. Institute of Computer Science, University of Hildesheim, Hildesheim, Germany

    Ruth Janning

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© 2014 Springer International Publishing Switzerland

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Ritze, D., Eckert, K. (2014). Data Enrichment in Discovery Systems Using Linked Data. In: Spiliopoulou, M., Schmidt-Thieme, L., Janning, R. (eds) Data Analysis, Machine Learning and Knowledge Discovery. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-01595-8_49

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