scholarly journals 23. What is at stake in data visualization? A feminist critique of the rhetorical power of data visualizations in the media

2020 ◽  
pp. 391-406
Keyword(s):  
Data Visualization ◽  
Feminist Critique ◽  
The Media ◽  
Data Visualizations

scholarly journals What is at stake in data visualization? A feminist critique of the rhetorical power of data visualizations in the media

2020 ◽  
Author(s):  
Rosemary Lucy Hill
Keyword(s):  
Data Visualization ◽  
Ethical Issues ◽  
Numerical Data ◽  
Feminist Critique ◽  
The World ◽  
The Media ◽  
Social And Ethical Issues ◽  
Contextual Detail ◽  
Data Visualizations

Data visualizations are powerful semiotic resources, which, it is sometimes claimed, have the power to change the world. This chapter argues that to understand this power we need to consider the uses to which visualizations have been put. Using visualizations relating to abortion as a case study alongside Klein and D’Ignazio’s notion of a ‘Bring Back the Bodies’ in data visualization, I argue that visualizations tell a narrow story, removing contextual detail and omitting to ask questions important to women’s health. To grasp the significance of this I propose a new body issue: the neglect of the viewer and those affected by decisions taken based on visualized data. Far from being a simple device to graphically display numerical data, therefore, there are important social and ethical issues at stake in data visualization.

A Feminist Critique of Representations of Potentially Coerced Women

2016 ◽  
Author(s):  
Charlotte Barlow
Keyword(s):  
Male Partner ◽  
Media Representation ◽  
Feminist Critique ◽  
Media Discourse ◽  
Potential Influence ◽  
Women's Representation ◽  
Women’S Representation ◽  
Media Construction ◽  
The Media ◽  
Offending Behaviour

This chapter discusses the media construction of women co-offenders and their relationship with their male partner/ co-offender, using the case/ court file material as a comparative tool. It particularly considers the ways in which the women’s representation served to minimise and discredit their perspectives and defence, particularly in relation to the potential influence of their relationship with their male partner on their offending behaviour. It also considers the ways in which the women’s suggestions of coercion or coercive techniques (at varying levels) by their male partner were constructed, particularly in media discourse. In doing so, the chapter is divided into a number of key themes, such as ‘bad women’ and ‘equally bad or worse’. It is important to note that the themes apply to the women at varying levels and the extent to which they were evident in the women’s legal and media representation will be discussed.

scholarly journals Data Visualization + Scrollytelling for Election News Stories : Challenges and Perspectives

2019 ◽  
Author(s):  
Jean-Philippe Corbeil ◽  
Florent Daudens ◽  
Thomas Hurtut
Keyword(s):  
Data Visualization ◽  
French Language ◽  
Daily Newspaper ◽  
Canadian French ◽  
News Stories ◽  
The Past ◽  
Narrative Format ◽  
Election News ◽  
Data Visualizations

This visual case study is conducted by Le Devoir, a Canadian french-language independent daily newspaper gathering around 50 journalists and one million readers every week. During the past twelve months, in collaboration with Polytechnique Montreal, we investigated a scrollytelling format strongly relying on combined series of data visualizations. This visual case study will specifically present one of the news stories we published, which communicates electoral results the day after the last Quebec general election. It gathers all the lessons that we learnt from this experience, the challenges that we tackled and the perspectives for the future. Beyond the specific electoral context of this work, these conclusions might be useful for any practitioner willing to communicate data visualization based stories, using a scrollytelling narrative format.

What we talk about when we talk about beautiful data visualizations

2020 ◽  
Author(s):  
Sara Brinch
Keyword(s):  
Data Visualization ◽  
Best Practice ◽  
Visualization Design ◽  
Data Visualizations

‘Beautiful’ is an adjective often used in descriptions of well-designed data visualizations. How the concept is used, however, reveals that it is applied to characterize a variety of qualities. Going beyond mere descriptions, the use of the concept also lays bare a certain ambivalence among scholars and practitioners towards how beauty matters, and which means it serves in data visualization. Interrogating ‘beautiful’ as a characterizing word, combined with a study of cases of ‘best practice’ used as examples of beautiful visualizations in various discourses, this chapter presents an analysis of what is regarded as beautiful within the field of data visualization design. This, in turn, can inform the understanding of what beauty means in visualizing data, in the purpose of facilitating the viewer’s comprehension and engagement.

The political significance of data visualization: Four key perspectives

2020 ◽  
Author(s):  
Torgeir Uberg Nærland
Keyword(s):  
Social Theory ◽  
Data Visualization ◽  
Status Quo ◽  
Public Deliberation ◽  
The Political ◽  
Progressive Change ◽  
The Status ◽  
Data Visualizations

Practitioners and scholars alike assume that data visualization can have political significance—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 significant. These perspectives imply differing notions of both ‘politics’ and ‘significance’. Drawing upon political and social theory, this chapter identifies 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 significance.

scholarly journals Data visualization literacy: Definitions, conceptual frameworks, exercises, and assessments

2019 ◽  
Vol 116 (6) ◽  
pp. 1857-1864 ◽  
Author(s):  
Katy Börner ◽  
Andreas Bueckle ◽  
Michael Ginda
Keyword(s):  
Data Visualization ◽  
Procedural Knowledge ◽  
Information Age ◽  
Current Data ◽  
Mathematical Literacy ◽  
Theoretical Frameworks ◽  
Core Concepts ◽  
Assessment Measures ◽  
Data Visualizations ◽  
Write Text

In the information age, the ability to read and construct data visualizations becomes as important as the ability to read and write text. However, while standard definitions and theoretical frameworks to teach and assess textual, mathematical, and visual literacy exist, current data visualization literacy (DVL) definitions and frameworks are not comprehensive enough to guide the design of DVL teaching and assessment. This paper introduces a data visualization literacy framework (DVL-FW) that was specifically developed to define, teach, and assess DVL. The holistic DVL-FW promotes both the reading and construction of data visualizations, a pairing analogous to that of both reading and writing in textual literacy and understanding and applying in mathematical literacy. Specifically, the DVL-FW defines a hierarchical typology of core concepts and details the process steps that are required to extract insights from data. Advancing the state of the art, the DVL-FW interlinks theoretical and procedural knowledge and showcases how both can be combined to design curricula and assessment measures for DVL. Earlier versions of the DVL-FW have been used to teach DVL to more than 8,500 residential and online students, and results from this effort have helped revise and validate the DVL-FW presented here.

scholarly journals Aesthetics and Clarity in Information Visualization: The Designer’s Perspective

Arts ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 72
Author(s):  
Annemarie Quispel ◽  
Alfons Maes ◽  
Joost Schilperoord
Keyword(s):  
Mass Media ◽  
Data Visualization ◽  
Information Visualization ◽  
Information Design ◽  
Future Research ◽  
Good Design ◽  
The Public ◽  
Objective Information ◽  
Data Visualizations ◽  
Important Design

Designers are increasingly involved in creating ‘popular’ data visualizations in mass media. Scientists in the field of information visualization propose collaborations between designers and scientists in popular data visualization. They assume that designers put more emphasis on aesthetics than on clarity in their representation of data, and that they aim to convey subjective, rather than objective, information. We investigated designers’ criteria for good design for a broad audience by interviewing professional designers and by reviewing information design handbooks. Additionally, we investigated what might make a visualization aesthetically pleasing (attractive) in the view of the designers. Results show that, according to the information designers, clarity and aesthetics are the main criteria, with clarity being the most important. They aim to objectively inform the public, rather than conveying personal opinions. Furthermore, although aesthetics is considered important, design literature hardly addresses the characteristics of aesthetics, and designers find it hard to define what makes a visualization attractive. The few statements found point at interesting directions for future research.

Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors

2015 ◽  
Vol 15 (3) ◽  
pp. 198-213 ◽  
Author(s):  
Katy Börner ◽  
Adam Maltese ◽  
Russell Nelson Balliet ◽  
Joe Heimlich
Keyword(s):  
Data Visualization ◽  
Informal Education ◽  
Science Museum ◽  
Science Museums ◽  
Museum Visitors ◽  
Hard Time ◽  
Phase Study ◽  
The Media ◽  
Multi Phase ◽  
Information Visualizations

In the information age, a person’s ability to read and make data visualizations is nearly as important as being able to read and write text. This article reports the results of a multi-phase study conducted in informal learning environments in three US science museums. The goal of the study was to determine the familiarity of youth and adult museum visitors with different visualization types. To address this, a total of 273 visitors were shown 5 out of 20 different visualizations that included two charts, five maps, eight graphs, and five network layouts. They were asked to judge the familiarity of the visualization, provide information on how to read it, and provide a name and identify typical locations where they would encounter the data display and possible data sources that might be visualized in this way. The results show that while most participants have a strong interest in science, math, and art, many have a hard time naming and interpreting visualizations. Participants in this study commonly encounter visualizations in school, in books, at work, on the Internet, and in the news. Overall, they were more familiar with basic charts, maps, and graphs, but very few are familiar with network layouts and most have no ability in reading network visualizations. When asked how they would interpret the visualizations, most participants pointed to superficial features such as color, lines, or text as important to developing understanding. Overall, we found that participants were interested in the visualizations we presented to them, but had significant limitations in identifying and understanding them. The results substantiate intuitions shared by many regarding the rather low level of data visualization literacy of general audiences. We hope they will help catalyze novel research on the development of easy-to-use yet effective visualizations with standardized names and guaranteed properties that can be readily used by those interested to understand and solve real-world problems. The results also have implications for how information visualizations are taught and used in formal and informal education, the media, or in different professions.

scholarly journals Dynamic Data Visualizations to Enhance Insight and Communication Across the Lifecycle of a Scientific Project

2021 ◽  
Author(s):  
Kristina Wiebels ◽  
David Moreau
Keyword(s):  
Data Visualization ◽  
Web Applications ◽  
Scientific Communication ◽  
R Language ◽  
Challenges And Opportunities ◽  
Recent Developments ◽  
Data Points ◽  
Scientific Project ◽  
Active Exploration ◽  
Data Visualizations

In scientific communication, figures are typically rendered as static displays. This often prevents active exploration of the underlying data, for example to gauge the influence of particular data points or of particular analytic choices. Yet modern data visualization tools, from animated plots to interactive notebooks and reactive web applications, allow psychologists to share and present their findings in dynamic and transparent ways. In this tutorial, we present a number of recent developments to build interactivity and animations into scientific communication and publications, using examples and illustrations in the R language. In particular, we discuss when and how to build dynamic figures, with step-by-step reproducible code that can easily be extended to the reader’s own projects. We illustrate how interactivity and animations can facilitate insight and communication across a project lifecycle—from initial exchanges and discussions within a team to peer-review and final publication—and provide a number of recommendations to use dynamic visualizations effectively. We close with a reflection on how the scientific publishing model is currently evolving, and consider the challenges and opportunities this shift might bring along for data visualization.

scholarly journals Graph structures for data visualizations

2021 ◽  
Vol 6 (2) ◽  
pp. 24-31
Author(s):  
Stefana Janićijević ◽  
Vojkan Nikolić
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Data Types ◽  
Current State ◽  
Graph Structures ◽  
Big Data Visualization ◽  
Visualization Tools ◽  
Graph System ◽  
Data Visualizations

Networks are all around us. Graph structures are established in the core of every network system therefore it is assumed to be understood as graphs as data visualization objects. Those objects grow from abstract mathematical paradigms up to information insights and connection channels. Essential metrics in graphs were calculated such as degree centrality, closeness centrality, betweenness centrality and page rank centrality and in all of them describe communication inside the graph system. The main goal of this research is to look at the methods of visualization over the existing Big data and to present new approaches and solutions for the current state of Big data visualization. This paper provides a classification of existing data types, analytical methods, techniques and visualization tools, with special emphasis on researching the evolution of visualization methodology in recent years. Based on the obtained results, the shortcomings of the existing visualization methods can be noticed.

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