{"title":"Getting portals to behave","authors":"Christopher Olston, Allison Woodruff","doi":"10.1109/INFVIS.2000.885087","DOIUrl":null,"url":null,"abstract":"Data visualization environments help users understand and analyze their data by permitting interactive browsing of graphical representations of the data. To further facilitate understanding and analysis, many visualization environments have special features known as portals, which are sub-windows of a data canvas. Portals provide a way to display multiple graphical representations simultaneously, in a nested fashion. This makes portals an extremely powerful and flexible paradigm for data visualization. Unfortunately, with this flexibility comes complexity. There are over a hundred possible ways each portal can be configured to exhibit different behaviors. Many of these behaviors are confusing and certain behaviors can be inappropriate for a particular setting. It is desirable to eliminate confusing and inappropriate behaviors. The authors construct a taxonomy of portal behaviors and give recommendations to help designers of visualization systems decide which behaviors are intuitive and appropriate for a particular setting. They apply these recommendations to an example setting that is fully visually programmable and analyze the resulting reduced set of behaviors. Finally, the authors consider a real visualization environment and demonstrate some problems associated with behaviors that do not follow their recommendations.","PeriodicalId":399031,"journal":{"name":"IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings","volume":"105 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFVIS.2000.885087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Data visualization environments help users understand and analyze their data by permitting interactive browsing of graphical representations of the data. To further facilitate understanding and analysis, many visualization environments have special features known as portals, which are sub-windows of a data canvas. Portals provide a way to display multiple graphical representations simultaneously, in a nested fashion. This makes portals an extremely powerful and flexible paradigm for data visualization. Unfortunately, with this flexibility comes complexity. There are over a hundred possible ways each portal can be configured to exhibit different behaviors. Many of these behaviors are confusing and certain behaviors can be inappropriate for a particular setting. It is desirable to eliminate confusing and inappropriate behaviors. The authors construct a taxonomy of portal behaviors and give recommendations to help designers of visualization systems decide which behaviors are intuitive and appropriate for a particular setting. They apply these recommendations to an example setting that is fully visually programmable and analyze the resulting reduced set of behaviors. Finally, the authors consider a real visualization environment and demonstrate some problems associated with behaviors that do not follow their recommendations.