S. Hong, Min-Joon Yoo, Bonnie Chinh, Amy Han, S. Battersby, Juho Kim
{"title":"To Distort or Not to Distort: Distance Cartograms in the Wild","authors":"S. Hong, Min-Joon Yoo, Bonnie Chinh, Amy Han, S. Battersby, Juho Kim","doi":"10.1145/3173574.3174202","DOIUrl":null,"url":null,"abstract":"Distance Cartograms (DC) distort geographical features so that the measured distance between a single location and any other location on a map indicates absolute travel time. Although studies show that users can efficiently assess travel time with DC, distortion applied in DC may confuse users, and its usefulness \"in the wild\" is unknown. To understand how real world users perceive DC's benefits and drawbacks, we devise techniques that improve DC's presentation (preserving topological relationships among map features while aiming at retaining shapes) and scalability (presenting accurate live travel time). We developed a DC-enabled system with these techniques, and deployed it to 20 participants for 4 weeks. During this period, participants spent, on average, more than 50% of their time with DC as opposed to a standard map. Participants felt DC to be intuitive and useful for assessing travel time. They indicated intent in adopting DC in their real-life scenarios.","PeriodicalId":20512,"journal":{"name":"Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3173574.3174202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Distance Cartograms (DC) distort geographical features so that the measured distance between a single location and any other location on a map indicates absolute travel time. Although studies show that users can efficiently assess travel time with DC, distortion applied in DC may confuse users, and its usefulness "in the wild" is unknown. To understand how real world users perceive DC's benefits and drawbacks, we devise techniques that improve DC's presentation (preserving topological relationships among map features while aiming at retaining shapes) and scalability (presenting accurate live travel time). We developed a DC-enabled system with these techniques, and deployed it to 20 participants for 4 weeks. During this period, participants spent, on average, more than 50% of their time with DC as opposed to a standard map. Participants felt DC to be intuitive and useful for assessing travel time. They indicated intent in adopting DC in their real-life scenarios.