LinkedPipes ETL: Evolved Linked Data Preparation

  • Jakub KlímekEmail author
  • Petr Škoda
  • Martin Nečaský
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9989)


As Linked Data gains traction, the proper support for its publication and consumption is more important than ever. Even though there is a multitude of tools for preparation of Linked Data, they are still either quite limited, difficult to use or not compliant with recent W3C Recommendations. In this demonstration paper, we present LinkedPipes ETL, a lightweight, Linked Data preparation tool. It is focused mainly on smooth user experience including mobile devices, ease of integration based on full API coverage and universal usage thanks to its library of components. We build on our experience gained by development and use of UnifiedViews, our previous Linked Data ETL tool, and present four use cases in which our new tool excels in comparison.


Linked Data RDF ETL Transformation 


  1. 1.
    Knap, T., Škoda, P., Klímek, J., Nečaký, M.: UnifiedViews: towards ETL tool for simple yet powerfull RDF data management. In: Proceedings of the Dateso 2015 Annual International Workshop on DAtabases, TExts, Specifications and Objects, Nepřívěc u Sobotky, Jičín, Czech Republic, 14 April 2015, pp. 111–120 (2015)Google Scholar
  2. 2.
    Thellmann, K., Orlandi, F., Auer, S.: LinDA - visualising and exploring linked data. In: Proceedings of the Posters and Demos Track of 10th International Conference on Semantic Systems - SEMANTiCS 2014, Leipzig, 9 (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Jakub Klímek
    • 1
    • 2
    • 3
    Email author
  • Petr Škoda
    • 1
    • 2
  • Martin Nečaský
    • 1
  1. 1.Faculty of Mathematics and PhysicsCharles University in PraguePraha 1Czech Republic
  2. 2.University of Economics, Prague Praha 3Czech Republic
  3. 3.Faculty of Information TechnologyCzech Technical University in PraguePraha 6Czech Republic

Personalised recommendations