A LOD Backend Infrastructure for Scientific Search Portals

  • Benjamin ZapilkoEmail author
  • Katarina Boland
  • Dagmar Kern
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10843)


In recent years, Linked Data became a key technology for organizations in order to publish their data collections on the web and to connect it with other data sources on the web. With the ongoing change in the research infrastructure landscape where an integrated search for comprehensive research information gains importance, organizations are challenged to connect their historically unconnected databases with each other. In this article, we present a Linked Open Data based backend infrastructure for a scientific search portal which is set as an additional layer between unconnected non-RDF data collections and makes the links between datasets visible and usable for retrieval. In addition, Linked Data technologies are used in order to organize different versions and aggregations of datasets. We evaluate the in-use application of our approach in a scientific search portal for the social sciences by investigating the benefit of links between different data sources in a user study.


Search Portal Linked Open Data (LOD) Elasticsearch Index Research Data Repository Database Link 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Parts of the approach presented in this paper have been developed in the InFoLiS project funded by DFG (SU 647/2-1 and MA 5334/1-2). The concept of the LOD backend infrastructure has been created by Benjamin Zapilko and Katarina Boland in the internally funded project LOD infrastructure. All extensions have been developed by Katarina Boland. The user study has been conducted during the development of the GESIS search by Dagmar Kern. The GESIS search portal has been developed by Daniel Hienert.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.GESIS - Leibniz-Institute for the Social SciencesCologneGermany

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