Automatic suggestions to improve the quality of scatterplots during its creation

A case study of semantic-based visualization


  • Dana Urribarri VyGLab (UNS-CICPBA), Departamento de Ciencia e Ingenierı́a de la Computación, Universidad Nacional del Sur, Bahı́a Blanca, CP8000, Argentina
  • Martín L Larrea, Dr. VyGLab (UNS-CICPBA), Departamento de Ciencia e Ingenierı́a de la Computación, Universidad Nacional del Sur, Bahı́a Blanca, CP8000, Argentina
  • Silvia M Castro, Dra. VyGLab (UNS-CICPBA), Departamento de Ciencia e Ingenierı́a de la Computación, Universidad Nacional del Sur, Bahı́a Blanca, CP8000, Argentina



ontology, scatterplot, semantic-based visualization, semantic reasoner, visualization quality prediction


The visualization process is a very complex exploration activity and, even for skilled users, it can be difficult to produce an effective visualization. The result of such process depends on the user's decisions along it. One way to improve the probability of achieving a useful outcome is to assist the user in the configuration and preparation of the visualization. Our proposal consists in live suggestions on how to improve the visualization. These live suggestions are based on the user decisions, and achieved by the integration of semantic reasoning into the visualization process. In this paper, we present a case study for scatterplots visualization that combines ontologies with a semantic reasoner and helps the user in the generation of an effective visualization.


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How to Cite

Urribarri, D., Larrea, M. L., & Castro, S. M. (2019). Automatic suggestions to improve the quality of scatterplots during its creation: A case study of semantic-based visualization. Journal of Computer Science and Technology, 19(2), e10.



Original Articles