Visual discovery by design

Ryan, Lindy

doi:10.1016/b978-0-12-803844-4.00012-1

Cited by 4 publications

(9 citation statements)

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“…Neben diesen Definitionsversuchen hat sich in der Literatur keine eindeutige Definition des Begriffs durchgesetzt. Basierend auf den verschiedenen Perspektiven und hervorgehobenen Aspekten (Ryan 2016 ; Vermeulen 2018 ; Vora 2019 ; Dykes 2016 ) des Data Storytellings kann diese jedoch als Prozess der Informationsaufbereitung und -darstellung von Ergebnissen einer Datenanalyse zur Motivation einer Entscheidung oder Handlung in einer der Zielgruppe entsprechenden Sprache und Visualisierung verstanden werden. Daraus gehen bereits drei wichtige Elemente des Data Storytellings hervor: Die Daten bzw.…”

Section: Data Storytellingunclassified

“…Sie besteht in der Regel aus der Ausgangssituation („in der Vergangenheit“), dem Höhe- und/oder Wendepunkt („dann passiert etwas“) und dem Ende („als Ergebnis“) (Callahan 2016 ). Nach Ryan ( 2016 ) kann zwischen acht Handlungsgerüsten einer Data Story unterschieden werden (vgl. Tab.…”

Section: Data Storytellingunclassified

“…Es geht hierbei primär darum zu verstehen, dass es in Daten nicht zwangsläufig eine Wahrheit gibt und daher der Kontext eine wichtige Rolle einnimmt. Die Daten sowie deren visuelle Darstellung sollten dementsprechend sorgfältig überdacht werden, um eine starke Botschaft präsentieren zu können (Ryan 2016 ). Auch Bladt und Filbin ( 2013 ) argumentieren, dass nur diejenigen Daten einbezogen werden sollten, die sich auf Schlüsselkennzahlen des Unternehmens auswirken und somit auf Daten verzichtet wird, welche die Problemstellung nicht beantworten.…”

Section: Die Erfolgsfaktoren Von Data Storytellingunclassified

“…Auch Bladt und Filbin ( 2013 ) argumentieren, dass nur diejenigen Daten einbezogen werden sollten, die sich auf Schlüsselkennzahlen des Unternehmens auswirken und somit auf Daten verzichtet wird, welche die Problemstellung nicht beantworten. Es muss jedoch immer evaluiert werden, ob bei der richtigen Daten- und Visualisierungsauswahl kein falsches Verständnis vermittelt wird (Ryan 2016 ). In Abb.…”

Section: Die Erfolgsfaktoren Von Data Storytellingunclassified

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Data Storytelling als kritischer Erfolgsfaktor von Data Science

Neifer

Lawo

Bossauer

et al. 2020

HMD

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Due to the ongoing digitalization and the Big Data trend, an increasing amount of data is available. This results in many potentials-especially for companies. The ability to cope with and evaluate this data is reflected in the role of the data scientist, which is one of the most popular jobs at present. However, challenges arise from the integration of data into corporate strategy and culture. For example, complex data and analysis results must be communicated to stakeholders who are not data-affine. Data storytelling plays a decisive role here, because to use data to initiate change, understanding and motivation for the issue must first be created for every target group. However, data storytelling is still a niche topic. This article uses a systematic literature analysis to derive the success factors of data storytelling for an effective and efficient communication of data to support Data Scientists in research and practice in communicating data and results.

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Section: Data Storytellingunclassified

Section: Die Erfolgsfaktoren Von Data Storytellingunclassified

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Data Storytelling als kritischer Erfolgsfaktor von Data Science

Neifer

Lawo

Bossauer

et al. 2020

HMD

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“…A context of graphing time provides a unifying theme for the corpus in Aigner et al 9 The history of tree-based visualizations in Lima 14 covers historical depth and breadth (with the earliest dated c. 2250 BCE) which supports a classification of such visualizations. Others take a different approach to discussions of historical context including: scientific objectivity in visualization and artistic visualization on case studies dating from the 18th century, 15 histories of visual communication encompassing a wider variety of visual mediums than typical visualization examples including symbolic pictures, written languages, illustrations and photography, 16 statues, sculptures, paintings, theater, and symbols. 17 Selected visualizations in history appear commonly as they are described in multiple sources, for example, the Fever Chart of Carl August Wunderlich 9,18,19 among others, contributing to the popularity of such visualization examples.…”

Section: Introductionmentioning

confidence: 99%

Open our visualization eyes, individualization: On Albrecht Dürer’s 1515 wood cut celestial charts

d’Auriol

2019

Information Visualization

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The position that visualization is an intimate part of human existence and associated with the human species is advanced in this work: visualization abounds delimited by the space of individuality across human history. Visualization involves two complementary aspects of the uniqueness deemed of individuals: individualization reflects individuals’ capabilities and personalization reflects designs that seek compatibility with individuals’ capabilities. This has a number of implications upon the design and evaluation of visualizations. For one, a suitable visualization model that expresses individualization and personalization is needed: a brief survey of models is presented. For another, addressing intellectual uniqueness requires deep analysis and selective objective balance due to the potentially humongous number of unique ideas that support visualization design and viewer experiences. The Engineering Insightful Serviceable Visualizations model is selected as a guide for a comprehensive visualization evaluation of Albrecht Dürer’s 1515 celestial charts. Motivating this choice of visualization is its significance as the first notable and influential European star chart intended for scientific use and mass viewership, and as a blending of science and art. In addition, there is a lack of discussion concerning this particular visualization in the visualization literature. Concluding remarks suggest the significance of approaching visualization from this point-of-view.

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Students’ multimodal knowledge sharing in school: Spatial repertoires and semiotic assemblages

Stenliden

Nissen

2021

Educ Inf Technol

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In a world ‘flooded’ with data, students in school need adequate tools as Visual Analytics (VA), that easily process mass data, give support in drawing advanced conclusions and help to make informed predictions in relation to societal circumstances. Methods for how the students’ insights may be reformulated and presented in ‘appropriate’ modes are required as well. Therefore, the aim in this study is to analyse elementary school students’ practices of communicating visual discoveries, their insights, as the final stage in the knowledge-building process with an VA-application for interactive data visualization. A design-based intervention study is conducted in one social science classroom to explore modes for students presentation of insights, constructed from the interactive data visualizations. Video captures are used to document 30 students’ multifaceted presentations. The analyses are based on concepts from Pennycook (2018) and Deleuze and Guattari (1987). To account for how different modes interact, when students present their findings, one significant empirical sequence is described in detail. The emerging communicative dimensions (visual-, bodily- and verbal-) are embedded within broad spatial repertoires distributing flexible semiotic assemblages. These assemblages provide an incentive for the possibilities of teachers’ assessments of their students’ knowledge outcomes.

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Visual discovery by design

Cited by 4 publications

References 0 publications

Data Storytelling als kritischer Erfolgsfaktor von Data Science

Data Storytelling als kritischer Erfolgsfaktor von Data Science

Open our visualization eyes, individualization: On Albrecht Dürer’s 1515 wood cut celestial charts

Students’ multimodal knowledge sharing in school: Spatial repertoires and semiotic assemblages

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