scholarly journals Exploring narrativity in data visualization in journalism

2020 ◽  
Author(s):  
Wibke Weber
Keyword(s):  
Data Visualization ◽  
Corpus Analysis ◽  
Temporal Dimension ◽  
News Stories ◽  
Visual Elements ◽  
Key Terms ◽  
Data Visualizations

Many news stories are based on data visualization, and storytelling with data has become a buzzword in journalism. But what exactly does storytelling with data mean? When does a data visualization tell a story? And what are narrative constituents in data visualization? This chapter first defines the key terms in this context: story, narrative, narrativity, showing and telling. Then, it sheds light on the various forms of narrativity in data visualization and, based on a corpus analysis of 73 data visualizations, describes the basic visual elements that constitute narrativity: the instance of a narrator, sequentiality, temporal dimension, and tellability. The paper concludes that understanding how data are transformed into visual stories is key to understanding how facts are shaped and communicated in society.

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.

scholarly journals Metáforas e gráficos pictórico-esquemáticos de Nigel Holmes | Nigel Holme’s metaphors and pictorial-schematic charts

2019 ◽  
Vol 16 (3) ◽  
pp. 330-348
Author(s):  
Ricardo Oliveira da Cunha Lima
Keyword(s):  
Data Visualization ◽  
Cognitive Linguistics ◽  
Numerical Data ◽  
Information Design ◽  
Point Of View ◽  
Figures Of Speech ◽  
Visual Elements ◽  
Visual Metaphors ◽  
Graphic Language ◽  
Data Visualizations

Neste artigo, abordaremos metáforas visuais utilizadas na visualização de dados da infografia do célebre designer Nigel Holmes. Isto foi feito mediante o diálogo com a linguística cognitiva e a retórica visual, pela ótica da teoria de design da informação. Para tanto, nossa abordagem é embasada na teoria das metáforas cognitivas, marcadas pelos estudos de Lakoff e Johnson (1980), e a tradição de estudos de figuras de linguagem visual. Nesta análise utilizamos uma taxonomia de figuras de linguagem pictóricas utilizadas em gráficos estatísticos (LIMA, 2018). Ao analisarmos as metáforas pictóricas utilizadas por Holmes, observamos que este designer tem a tendência a sobrepor elementos pictóricos a elementos esquemáticos em seus gráficos estatísticos. Nós cunhamos esta mescla de modalidades gráficas de gráficos pictórico-esquemáticos. Este uso de elementos pictóricos, muitas vezes, humorísticos sobrepostos a dados numéricos precisos foi duramente combatida por teóricos do design da informação como Edward Tufte, na década de 1980. Estes elementos pictóricos foram chamados de chartjunk. Este termo tem servido como uma crítica à elementos visuais consideradas supérfluos em nome de uma abordagem mais neutra na infografia e visualização de dados. No entanto, procuramos entender a escolha do uso de metáforas visuais por Holmes como uma abordagem que não se limita a uma suposta neutralidade de linguagem gráfica.*****In this article, the focus is on visual metaphors used in Nigel Holmes’ data visualizations present in his infographics. This analysis was accomplished by approaching the theory of cognitive linguistics and visual rhetoric from the point of view of information design. Our study is based on the theory of cognitive metaphors, notably the work of Lakoff and Johnson (1980), and the study of figures of speech in visual language. In this analysis, we used a taxonomy of figures of speech for pictorial language in data visualization (LIMA, 2018). When analyzing the pictorial metaphors used by Holmes, we observe that this designer tends to overlap pictorial elements on schematic ones in his statistical charts. We coined this mix of graphic modalities: pictorial-schematic charts (gráficos pictórico-esquemáticos). This use of pictorial elements, often humorous, overlapping precise numerical data was harshly opposed by information design theorists such as Edward Tufte in the 1980s. These pictorial elements were called chartjunk. This term has served as a criticism of visual elements considered superfluous in the name of a more neutral approach to infographics and data visualization. However, we seek to understand Holmes' choice of using visual metaphors as an approach that is not limited to a supposedly neutral graphic language.

Reducing misperceptions through news stories with data visualization: The role of readers’ prior knowledge and prior beliefs

Journalism ◽  
2021 ◽  
pp. 146488492110287
Author(s):  
Paul Mena
Keyword(s):  
Experimental Design ◽  
Prior Knowledge ◽  
Data Visualization ◽  
Accurate Information ◽  
Graphical Representations ◽  
Prior Beliefs ◽  
News Stories ◽  
Issue Involvement

Amid the global discussion on ways to fight misinformation, journalists have been writing stories with graphical representations of data to expose misperceptions and provide readers with more accurate information. Employing an experimental design, this study explored to what extent news stories correcting misperceptions are effective in reducing them when the stories include data visualization and how influential readers’ prior beliefs, issue involvement and prior knowledge may be in that context. The study found that the presence of data visualization in news articles correcting misperceptions significantly enhanced the reduction of misperceptions among news readers with less than average prior knowledge about an issue. In addition, it was found that prior beliefs had a significant effect on news readers’ misperceptions regardless of the presence or absence of data visualization. In this way, this research offers some support for the notion that data visualization may be useful to decrease misperceptions under certain circumstances.

scholarly journals What a line can say : Investigating the semiotic potential of the connecting line in data visualizations

2020 ◽  
Author(s):  
Verena Elisabeth Lechner
Keyword(s):  
Empirical Research ◽  
Basic Function ◽  
Visual Elements ◽  
Data Visualizations ◽  
Semiotic Theory

The line is a graphical element widely used in data visualizations, its purpose often being to signal a connection between other visual elements. Based on social semiotic theory, this article investigates what semiotic functions connecting lines can have and how these functions can be related to variations in form. The results show that, in addition to the basic function of connecting elements, such lines can also indicate the level of certainty, direct the viewer to read the information either as a narrative or a conceptual claim, indicate patterns of cohesion, and regulate the viewer’s position. These findings allow for further empirical research on the formation of visual conventions.

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.

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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