Goal-Based Selection of Visual Representations for Big Data Analytics

  • Matteo Golfarelli
  • Tommaso Pirini
  • Stefano RizziEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10651)


The H2020 TOREADOR Project adopts a model-driven architecture to streamline big data analytics and make it widely available to companies as a service. Our work in this context focuses on visualization, in particular on how to automate the translation of the visualization objectives declared by the user into a suitable visualization type. To this end we first define a visualization context based on seven prioritizable coordinates for assessing the user’s objectives and describing the data to be visualized; then we propose a skyline-based technique for automatically translating a visualization context into a set of suitable visualization types. Finally, we evaluate our approach on a real use case excerpted from the pilot applications of TOREADOR.


Big data Visual analytics Skyline queries 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Matteo Golfarelli
    • 1
    • 2
  • Tommaso Pirini
    • 1
  • Stefano Rizzi
    • 1
    • 2
    Email author
  1. 1.DISIUniversity of BolognaBolognaItaly
  2. 2.CINIRomaItaly

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