{"title":"13. Data visualization literacy: A feminist starting point","authors":"C. D’Ignazio, Rahul Bhargava","doi":"10.1515/9789048543137-017","DOIUrl":null,"url":null,"abstract":"We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineeering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces where, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives’.","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Visualization in Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/9789048543137-017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineeering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces where, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives’.