Advertisement A Platform for Semantically Representing and Analyzing Open Fiscal Data

  • Fathoni A. MusyaffaEmail author
  • Lavdim Halilaj
  • Yakun Li
  • Fabrizio Orlandi
  • Hajira Jabeen
  • Sören Auer
  • Maria-Esther Vidal
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10845)


Budget and spending data are among the most published Open Data datasets on the Web and continuously increasing in terms of volume over time. These datasets tend to be published in large tabular files – without predefined standards – and require complex domain and technical expertise to be used in real-world scenarios. Therefore, the potential benefits of having these datasets open and publicly available are hindered by their complexity and heterogeneity. Linked Data principles can facilitate integration, analysis and usage of these datasets. In this paper, we present (OBEU), a Linked Data -based platform supporting the entire open data life-cycle of budget and spending datasets: from data creation to publishing and exploration. The platform is based on a set of requirements specifically collected by experts in the budget and spending data domain. It follows a micro-services architecture that easily integrates many different software modules and tools for analysis, visualization and transformation of data. Data is represented according to a logical model for open fiscal data which is translated into both RDF data and a tabular data formats. We demonstrate the validity of the implemented OBEU platform with real application scenarios and report on a user study conducted to confirm its usability.



The work presented is co-funded by the EU H2020 for the project (GA no. 645833), Fathoni Musyaffa is supported by a DAAD scholarship.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Fathoni A. Musyaffa
    • 1
    Email author
  • Lavdim Halilaj
    • 1
    • 2
  • Yakun Li
    • 2
  • Fabrizio Orlandi
    • 1
    • 2
  • Hajira Jabeen
    • 1
  • Sören Auer
    • 3
    • 4
  • Maria-Esther Vidal
    • 3
    • 5
  1. 1.University of BonnBonnGermany
  2. 2.Fraunhofer IAISSankt AugustinGermany
  3. 3.TIB Leibniz Information Center Science and TechnologyHannoverGermany
  4. 4.L3S Research CenterUniversity of HannoverHannoverGermany
  5. 5.Simón Bolívar UniversityCaracasVenezuela

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