Using Spatiotemporal Information to Integrate Heterogeneous Biodiversity Semantic Data

  • Flor AmanquiEmail author
  • Ruben Verborgh
  • Erik Mannens
  • Rik Van de Walle
  • Dilvan Moreira
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9671)


Biodiversity is essential to life on Earth and motivates many efforts to collect data about species. These data are collected in different places and published in different formats. Researchers use it to extract new knowledge about living things, but it is difficult to retrieve, combine and integrate data sources from different places. This work will investigate how to integrate biodiversity information from heterogeneous sources using Semantic Web technologies. Its main objective is to propose an architecture to link biodiversity data using mainly their spatiotemporal dimension, effectively search these linked data sets and test them using real use cases, defined with the help of biodiversity experts. It is also an important objective to propose a suitable provenance model that captures not only data origin but also temporal information. This architecture will be tested on a set of representative data from important Brazilian institutions that are involved in studies of biodiversity.


Semantic web Linked data Biodiversity 



The research activities described in this paper were funded by Ghent University, iMinds, the IWT-Flanders, the FWO-Flanders, and the European Union, and the FINCyT Science and Technology Program from Peru.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Flor Amanqui
    • 1
    • 2
    Email author
  • Ruben Verborgh
    • 1
  • Erik Mannens
    • 1
  • Rik Van de Walle
    • 1
  • Dilvan Moreira
    • 2
  1. 1.Data Science LabGhent University - IMindsGhentBelgium
  2. 2.SCC-ICMCUniversity of Sao PauloSao PauloBrazil

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