scholarly journals Data Visualization Design for NSFC Joint Fund Management

2021 ◽  
Vol 3 ◽  
pp. 1-1
Author(s):  
Zhao Jin ◽  
Tao Wang ◽  
Zhipeng Huang
Keyword(s):  
Data Visualization ◽  
Fund Management ◽  
Visualization Design

scholarly journals Research on the Application of Data Visualization Design in CBA League News

2021 ◽  
Vol 236 ◽  
pp. 05078
Author(s):  
Yi Sui ◽  
Honghai Zhang
Keyword(s):  
Data Analysis ◽  
Data Visualization ◽  
User Needs ◽  
Visual Data ◽  
Core Competitiveness ◽  
The Core ◽  
Visualization Design ◽  
Sports News ◽  
The Core Competitiveness ◽  
And Function

In the context of the era of intelligence, the capacity and function of data is expanding, and is playing an irreplaceable role in the field of sports news. This paper studies the data expression mode of sports news. From the point of user needs and the characteristics of visual data, this paper discusses the methods and suggestions of data visualization design in CBA league news, in an attempt to form an intuitive, efficient and convenient visual form of sports news, which can promote the multi-dimensional development of visual symbols in sports news, and promote the progress of data analysis and prediction. The data visualization has become the core competitiveness of sports news.

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.

scholarly journals The Spatial-Perceptual Design Space: A New Comprehension for Data Visualization

2007 ◽  
Vol 6 (4) ◽  
pp. 261-279 ◽  
Author(s):  
José Fernando Rodrigues ◽  
Agma JM Traina ◽  
Maria Cristina F. de Oliveira ◽  
Caetano Traina
Keyword(s):  
Visual Perception ◽  
Data Visualization ◽  
Design Space ◽  
Visual Analysis ◽  
Human Visual Perception ◽  
Conceptual Organization ◽  
Visualization Design

We revisit the design space of visualizations aiming at identifying and relating its components. In this sense, we establish a model to examine the process through which visualizations become expressive for users. This model has lead us to a taxonomy oriented to the human visual perception. The essence of this taxonomy provides natural criteria in order to delineate a novel understanding for the design space of visualizations. From such understanding, we elaborate a model for generalized design. The model poses an intuitive comprehension for the visualization design space departing from fundamental pre-attentive stimuli and from perceptual phenomena. The paper is presented as a survey, its structure introduces an alternative conceptual organization for the space of techniques concerning visual analysis.

Data visualization in chronic neurological and mental health condition self-management: a systematic review of user perspectives (Preprint)

2020 ◽  
Author(s):  
Ashley Polhemus ◽  
Jan Novak ◽  
Shazmin Majid ◽  
Sara Simblett ◽  
Stuart Bruce ◽  
...  
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Data Visualization ◽  
User Preferences ◽  
Health Conditions ◽  
Cochrane Library ◽  
Mental Health Conditions ◽  
Visualization Design ◽  
The Impact ◽  
Data Visualizations

BACKGROUND Remote measurement technology (RMT) such as mobile health devices and applications, are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, though little is known about visualization design preferences from the perspectives of those living with chronic conditions. OBJECTIVE Explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health. METHODS In this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, ACM Computer-Human Interface proceedings, and the Cochrane Library) for original articles published between January 2007 and February 2020 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised and extracted data underwent thematic synthesis. RESULTS We identified 28 eligible publications from 24 studies representing 11 conditions. Coded data coalesced into four themes: desire for data visualization, the impact of visualizations on condition management, visualizations as data reporting tools, and visualization design considerations. Data visualizations were viewed an integral part of users’ experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting, both between and within conditions. CONCLUSIONS When used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not “one-size-fits-all,” and it is important to engage with potential user during visualization design to understand when, how, and with whom the visualizations will be used to manage health.

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