@InProceedings{RodriguesBarbLopeBarb:2019:CoEfVi,
               author = "Rodrigues, Ariane Moraes Bueno and Barbosa, Gabriel Diniz 
                         Junqueira and Lopes, H{\'e}lio and Barbosa, Simone Diniz 
                         Junqueira",
          affiliation = "PUC-Rio and PUC-Rio and PUC-Rio and PUC-Rio",
                title = "Comparing the effectiveness of visualizations of different data 
                         distributions",
            booktitle = "Proceedings...",
                 year = "2019",
               editor = "Oliveira, Luciano Rebou{\c{c}}as de and Sarder, Pinaki and Lage, 
                         Marcos and Sadlo, Filip",
         organization = "Conference on Graphics, Patterns and Images, 32. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "information visualization, visualization tasks.",
             abstract = "The effectiveness of a data visualization depends on several 
                         factors, such as the visual encoding of its elements, the 
                         analytical task it aims to support, the dimensionality of the 
                         data, and even the data distribution. In this work, we report an 
                         empirical evaluation of common data visualizations, focusing on 
                         how different data distributions affect their effectiveness and 
                         the level of confidence users have when answering questions 
                         related to certain analytical task types. The study allowed us to 
                         assess to what extent some data visualizations are more effective 
                         than others, regardless of data distribution. We conclude that 
                         data visualization creators and algorithms need to consider the 
                         data distribution when generating data visualizations. From the 
                         results, we also propose recommendations for choosing a 
                         visualization when dealing with data distribution issues.",
  conference-location = "Rio de Janeiro, RJ, Brazil",
      conference-year = "28-31 Oct. 2019",
                  doi = "10.1109/SIBGRAPI.2019.00020",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2019.00020",
             language = "en",
                  ibi = "8JMKD3MGPEW34M/3U38PT8",
                  url = "http://urlib.net/ibi/8JMKD3MGPEW34M/3U38PT8",
           targetfile = "SIBGRAPI_2019___Ariane_Gabriel_H_lio_Simone.pdf",
        urlaccessdate = "2024, Apr. 28"
}