author = "Oliveira, Guilherme and Comba, Jo{\~a}o and Torchelsen, Rafael 
                         and Padilha, Maristela and Silva, Claudio",
          affiliation = "{UFRGS - Brazil} and {UFRGS - Brazil} and {UFFS - Brazil} and {IPA 
                         - Brazil} and {NYU-Poly - USA}",
                title = "Visualizing Running Races Through the Multivariate Time-Series of 
                         Multiple Runners",
            booktitle = "Proceedings...",
                 year = "2013",
               editor = "Boyer, Kim and Hirata, Nina and Nedel, Luciana and Silva, 
         organization = "Conference on Graphics, Patterns and Images, 26. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Time Series, Races.",
             abstract = "The recent widespread of heart rate (HR) monitors is allowing 
                         people to measure body response during and after exercise, which 
                         produces a collection of time-series on multivariate aspects, such 
                         as heartbeat, speed, geolocation, etc. Such monitoring can be 
                         extremely important for people with low fitness levels, since they 
                         are susceptible to cardiovascular diseases or other physical 
                         injuries when exercising at high heartbeat frequencies. Even 
                         though most monitors provide tools to export and display this 
                         information for each individual, the ability to visualize the 
                         collection of multiple runners in a given running race is mostly 
                         unexplored. In this work, we present a design study that aims to 
                         support analysis and answer several questions raised by an expert 
                         on exercise physiology about a given running race. We describe 
                         each visualization design and how they individually, or in 
                         collaboration, can be used to reveal interesting aspects of the 
                         data. We illustrate our results with use cases that provide 
                         evaluation and feedback about the visualization designs 
  conference-location = "Arequipa, Peru",
      conference-year = "Aug. 5-8, 2013",
             language = "en",
           targetfile = "paper.pdf",
        urlaccessdate = "2020, Nov. 25"