scholarly journals A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT

2018 ◽  
Author(s):  
Anamaria Crisan ◽  
Jennifer L. Gardy ◽  
Tamara Munzner
Keyword(s):  
Data Visualization ◽  
Design Space ◽  
Systematic Method ◽  
Genomic Epidemiology ◽  
Link Type ◽  
Research Areas ◽  
Visualization Tools ◽  
Visualization Design ◽  
Scientific Research Articles ◽  
Data Visualizations

AbstractMotivation:Data visualization is an important tool for exploring and communicating findings from genomic and healthcare datasets. Yet, without a systematic way of organizing and describing the design space of data visualizations, researchers may not be aware of the breadth of possible visualization design choices or how to distinguish between good and bad options.Results:We have developed a method that systematically surveys data visualizations using the analysis of both text and images. Our method supports the construction of a visualization design space that is explorable along two axes: why the visualization was created and how it was constructed. We applied our method to a corpus of scientific research articles from infectious disease genomic epidemiology and derived a Genomic Epidemiology Visualization Typology (GEViT) that describes how visualizations were created from a series of chart types, combinations, and enhancements. We have also implemented an online gallery that allows others to explore our resulting design space of visualizations. Our results have important implications for visualization design and for researchers intending to develop or use data visualization tools. Finally, the method that we introduce is extensible to constructing visualizations design spaces across other research areas.Availability:Our browsable gallery is available at http://gevit.net and all project code can be found at https://github.com/amcrisan/gevitAnalysisRelease

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 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.

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.

Data visualization as a communication tool

2015 ◽  
Vol 32 (2) ◽  
pp. 1-9 ◽  
Author(s):  
Susan Gardner Archambault ◽  
Joanne Helouvry ◽  
Bonnie Strohl ◽  
Ginger Williams
Keyword(s):  
Data Visualization ◽  
Complex Data ◽  
Data Display ◽  
Communication Tool ◽  
Online Data ◽  
Content Type ◽  
Institutional Accreditation ◽  
Scatter Plots ◽  
Visualization Tools ◽  
Visualization Design

Purpose – This paper aims to provide a framework for thinking about meaningful data visualization in ways that can be applied to routine statistics collected by libraries. Design/methodology/approach – An overview of common data display methods is provided, with an emphasis on tables, scatter plots, line charts, bar charts, histograms, pie charts and infographics. Research on “best practices” in data visualization design is presented; also provided is a comparison of free online data visualization tools. Findings – Different data display methods are best suited for different quantitative relationships. There are rules to follow for optimal data visualization design. Ten free online data visualization tools are recommended by the authors. Originality/value – Evidence-based libraries collect and use data to affect change and to support departmental and institutional accreditation standards. Proper data visualization allows libraries to communicate their message in a more compelling and interesting way, while assisting in the understanding of complex data.

scholarly journals Enhancing the operational value of snowpack models with visualization design principles

2020 ◽  
Vol 20 (6) ◽  
pp. 1557-1572
Author(s):  
Simon Horton ◽  
Stan Nowak ◽  
Pascal Haegeli
Keyword(s):  
Spatial Scales ◽  
Critical Role ◽  
Design Principles ◽  
Physical Models ◽  
Model Data ◽  
User Testing ◽  
Avalanche Forecasting ◽  
Cognitive Principles ◽  
Visualization Tools ◽  
Visualization Design

Abstract. Forecasting snow avalanches requires a reliable stream of field observations, which are often difficult and expensive to collect. Despite the increasing capability of simulating snowpack conditions with physical models, models have seen limited adoption by avalanche forecasters. Feedback from forecasters suggests that model data are presented in ways that are difficult to interpret and irrelevant to operational needs. We apply a visualization design framework to enhance the value of snowpack models to avalanche forecasters. An established risk-based avalanche forecasting workflow is used to define the ways forecasters solve problems with snowpack data. We suggest that model data be visualized in ways that directly support common forecasting tasks such as identifying snowpack features related to avalanche problems and locating avalanche problems in terrain at relevant spatial scales. Examples of visualizations that support these tasks and follow established perceptual and cognitive principles from the field of information visualization are presented. Interactive designs play a critical role in understanding these complex datasets and are well suited for forecasting workflows. Although extensive user testing is still needed to evaluate the effectiveness of these designs, visualization design principles open the door to more relevant and interpretable applications of snowpack model for avalanche forecasters. This work sets the stage for implementing snowpack models into visualization tools where forecasters can test their operational value and learn their capabilities and deficiencies.

scholarly journals Developing effective data visualization tools for nutrition: reflections on the design of a Nutrition Scorecard in Nigeria

2021 ◽  
Vol 5 ◽  
pp. 98
Author(s):  
Yashodhara Rana ◽  
Gianni Dongo ◽  
Caroline Snead ◽  
Grace Agi ◽  
Oluwagbenga Sadik ◽  
...  
Keyword(s):  
Data Visualization ◽  
Target Audience ◽  
Theory Of Change ◽  
Open Letter ◽  
Target Groups ◽  
Design Processes ◽  
Participatory Processes ◽  
Visualization Tools ◽  
Collaborative Efforts ◽  
Constructive Action

There has been a growing number of nutrition data visualization tools (DVTs) to monitor progress towards targets and encourage action. However, there are few documented examples of how to go about designing effective DVTs for nutrition-related audiences. In this Open Letter, we summarize reflections from collaborative efforts between the Nigeria Governors’ Forum (NGF) and the Data for Decisions to Expand Nutrition Transformation project (DataDENT) in 2019-2021 to design a sub-national nutrition scorecard that aims to hold Nigeria’s 36 Governors accountable to nutrition commitments. Our reflections add to an emerging body of work advocating for DVT design processes to develop a specific theory of change for how the DVT will influence target groups and achieve aims. Once the target audience is identified, it is important to create a strong engagement strategy to ensure that the DVT promotes constructive action. We also highlight the importance of identifying actionable indicators through participatory processes. We hope that these insights about collaborative DVT design can be applied by countries and institutions who want to develop similar tools to advance the nutrition agenda in their context.

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