Pub Date : 2020-12-31DOI: 10.1515/9789048543137-019
Arlene Archer, Travis M Noakes
This chapter investigates the semiotic and rhetorical strategies for realizing argument in data visualizations produced by second-year journalism students. The semiotic strategies include use of colour, typography, graphics, and the rhetorical strategies include establishing credibility and the use of citation. The effect of the underlying basis for comparison of data on the argument is examined, as are the selection and processing of data. The chapter investigates the semiotic encoding of ideational material and the ways relationships are established within the discourse communities constructed in the data visualizations. This way of looking at academic argument has important implications for teaching these text-types in higher education in order to produce critical citizens; both in terms of production and critical analysis.
{"title":"15. Multimodal academic argument in data visualization","authors":"Arlene Archer, Travis M Noakes","doi":"10.1515/9789048543137-019","DOIUrl":"https://doi.org/10.1515/9789048543137-019","url":null,"abstract":"This chapter investigates the semiotic and rhetorical strategies for realizing argument in data visualizations produced by second-year journalism students. The semiotic strategies include use of colour, typography, graphics, and the rhetorical strategies include establishing credibility and the use of citation. The effect of the underlying basis for comparison of data on the argument is examined, as are the selection and processing of data. The chapter investigates the semiotic encoding of ideational material and the ways relationships are established within the discourse communities constructed in the data visualizations. This way of looking at academic argument has important implications for teaching these text-types in higher education in order to produce critical citizens; both in terms of production and critical analysis.","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121085974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-017
C. D’Ignazio, Rahul Bhargava
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’.
{"title":"13. Data visualization literacy: A feminist starting point","authors":"C. D’Ignazio, Rahul Bhargava","doi":"10.1515/9789048543137-017","DOIUrl":"https://doi.org/10.1515/9789048543137-017","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":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125756074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-023
J. Gray
{"title":"19. The data epic : Visualization practices for narrating life and death at a distance","authors":"J. Gray","doi":"10.1515/9789048543137-023","DOIUrl":"https://doi.org/10.1515/9789048543137-023","url":null,"abstract":"","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126040879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-004
{"title":"Foreword: The dawn of a philosophy of visualization","authors":"","doi":"10.1515/9789048543137-004","DOIUrl":"https://doi.org/10.1515/9789048543137-004","url":null,"abstract":"","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133926323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-007
G. Aiello
This chapter is an overview of social semiotics as a productive framework for research on data visualization. It provides conceptual instruments that can be used to explore the relationship between the formal properties of data visualization and the meanings and practices that these may promote or hinder among users. In particular, the chapter argues that a social semiotic framework can be used to inventorize , situate , and transform visualization resources. Overall, it links descriptive, interpretive, and critical objectives to generate a framework aimed at understanding how data visualization ‘works’ from a formal standpoint, what meanings are consistently associated with particular semiotic resources, and how both key semiotic ‘rules’ and dominant meanings may be questioned and changed.
{"title":"3. Inventorizing, situating, transforming : Social semiotics and data visualization","authors":"G. Aiello","doi":"10.1515/9789048543137-007","DOIUrl":"https://doi.org/10.1515/9789048543137-007","url":null,"abstract":"This chapter is an overview of social semiotics as a productive framework for research on data visualization. It provides conceptual instruments that can be used to explore the relationship between the formal properties of data visualization and the meanings and practices that these may promote or hinder among users. In particular, the chapter argues that a social semiotic framework can be used to inventorize , situate , and transform visualization resources. Overall, it links descriptive, interpretive, and critical objectives to generate a framework aimed at understanding how data visualization ‘works’ from a formal standpoint, what meanings are consistently associated with particular semiotic resources, and how both key semiotic ‘rules’ and dominant meanings may be questioned and changed.","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124171818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-008
Torgeir Uberg Nærland
Practitioners and scholars alike assume that data visualization can have political signif icance—as vehicle for progressive change, manipulation, or maintaining the status quo. There are, however, a variety of ways in which we can think of data visualization as politically signif icant. These perspectives imply differing notions of both ‘politics’ and ‘signif icance’. Drawing upon political and social theory, this chapter identif ies and outlines four key perspectives: data visualization and 1) public deliberation, 2) ideology, 3) citizenship, and 4) as a political-administrative steering tool. The aim of this chapter is thus to provide a framework that helps clarify the various contexts, processes, and capacities through which data visualizations attain political signif icance.
{"title":"4. The political significance of data visualization: Four key perspectives 4. The political significance of data visualization: Four key perspectives","authors":"Torgeir Uberg Nærland","doi":"10.1515/9789048543137-008","DOIUrl":"https://doi.org/10.1515/9789048543137-008","url":null,"abstract":"Practitioners and scholars alike assume that data visualization can have political signif icance—as vehicle for progressive change, manipulation, or maintaining the status quo. There are, however, a variety of ways in which we can think of data visualization as politically signif icant. These perspectives imply differing notions of both ‘politics’ and ‘signif icance’. Drawing upon political and social theory, this chapter identif ies and outlines four key perspectives: data visualization and 1) public deliberation, 2) ideology, 3) citizenship, and 4) as a political-administrative steering tool. The aim of this chapter is thus to provide a framework that helps clarify the various contexts, processes, and capacities through which data visualizations attain political signif icance.","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127782798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-028
B. Ricker, M. Kraak, Y. Engelhardt
Maps are representations of the world. They offer summaries or simplifica-tions of data that are collected, attempt to reveal unknowns, to simplify and communicate complex spatial phenomena. Numerous decisions are made in the process of creating a map. Seemingly inconsequential variations of cartographic design decisions offer many ways to illustrate this process. We use an open dataset related to the United Nations Gender Inequality Index to demonstrate design decision points and their output. As governments are increasingly making data open to the public, and map-making tools and software are now more accessible online, these considerations are important both for those making and reading maps online.
{"title":"24. The power of visualization choices: Different images of patterns in space","authors":"B. Ricker, M. Kraak, Y. Engelhardt","doi":"10.1515/9789048543137-028","DOIUrl":"https://doi.org/10.1515/9789048543137-028","url":null,"abstract":"Maps are representations of the world. They offer summaries or simplifica-tions of data that are collected, attempt to reveal unknowns, to simplify and communicate complex spatial phenomena. Numerous decisions are made in the process of creating a map. Seemingly inconsequential variations of cartographic design decisions offer many ways to illustrate this process. We use an open dataset related to the United Nations Gender Inequality Index to demonstrate design decision points and their output. As governments are increasingly making data open to the public, and map-making tools and software are now more accessible online, these considerations are important both for those making and reading maps online.","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"R-26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115397281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-002
{"title":"List of figures","authors":"","doi":"10.1515/9789048543137-002","DOIUrl":"https://doi.org/10.1515/9789048543137-002","url":null,"abstract":"","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128745443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9789048543137-016
Elise Seip Tønnessen
This article explores the concept of literacy related to the use of data visualizations. Literacy is here understood as the ability to make sense from semiotic resources in an educational context. Theoretically the discussion is based in social semiotic theory on multimodality in the tradition of New Literacy Studies. Empirical examples are taken from observations in two Social Science classrooms in upper secondary school in Norway, where the students work with publicly available data visualizations to answer tasks designed by their teacher. The discussion sums up factors that affect reading and learning from such complex resources: taking time to explore axis system, variables, and digitally available options; questioning data; and contextualizing results. task of Our reveal a need to find teachable moments in school literacy practices. One when the were to change the axis variables. Those who had the
{"title":"12. What is visual-numeric literacy, and how does it work?","authors":"Elise Seip Tønnessen","doi":"10.1515/9789048543137-016","DOIUrl":"https://doi.org/10.1515/9789048543137-016","url":null,"abstract":"This article explores the concept of literacy related to the use of data visualizations. Literacy is here understood as the ability to make sense from semiotic resources in an educational context. Theoretically the discussion is based in social semiotic theory on multimodality in the tradition of New Literacy Studies. Empirical examples are taken from observations in two Social Science classrooms in upper secondary school in Norway, where the students work with publicly available data visualizations to answer tasks designed by their teacher. The discussion sums up factors that affect reading and learning from such complex resources: taking time to explore axis system, variables, and digitally available options; questioning data; and contextualizing results. task of Our reveal a need to find teachable moments in school literacy practices. One when the were to change the axis variables. Those who had the","PeriodicalId":437386,"journal":{"name":"Data Visualization in Society","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126486887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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