{"title":"数据优先的可视化设计研究","authors":"Michael Oppermann, T. Munzner","doi":"10.1109/BELIV51497.2020.00016","DOIUrl":null,"url":null,"abstract":"We introduce the notion of a data-first design study which is triggered by the acquisition of real-world data instead of specific stakeholder analysis questions. We propose an adaptation of the design study methodology framework to provide practical guidance and to aid transferability to other data-first design processes. We discuss opportunities and risks by reflecting on two of our own data-first design studies. We review 64 previous design studies and identify 16 of them as edge cases with characteristics that may indicate a data-first design process in action.","PeriodicalId":282674,"journal":{"name":"2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Data-First Visualization Design Studies\",\"authors\":\"Michael Oppermann, T. Munzner\",\"doi\":\"10.1109/BELIV51497.2020.00016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce the notion of a data-first design study which is triggered by the acquisition of real-world data instead of specific stakeholder analysis questions. We propose an adaptation of the design study methodology framework to provide practical guidance and to aid transferability to other data-first design processes. We discuss opportunities and risks by reflecting on two of our own data-first design studies. We review 64 previous design studies and identify 16 of them as edge cases with characteristics that may indicate a data-first design process in action.\",\"PeriodicalId\":282674,\"journal\":{\"name\":\"2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)\",\"volume\":\"204 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BELIV51497.2020.00016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Workshop on Evaluation and Beyond - Methodological Approaches to Visualization (BELIV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BELIV51497.2020.00016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We introduce the notion of a data-first design study which is triggered by the acquisition of real-world data instead of specific stakeholder analysis questions. We propose an adaptation of the design study methodology framework to provide practical guidance and to aid transferability to other data-first design processes. We discuss opportunities and risks by reflecting on two of our own data-first design studies. We review 64 previous design studies and identify 16 of them as edge cases with characteristics that may indicate a data-first design process in action.
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