LETTERS to the EDITORPublication bias

Examples are discussed to show the differences among discriminant analysis, logistic regression, and multiple regression. Chapter 6, “Multivariate Analysis of Variance,” presents advantages of multivariate analysis of variance (MANOVA) over univariate analysis of variance (ANOVA), discusses assumptions of MANOVA, and assesses validations of MANOVA assumptions and model estimation. The authors also discuss post hoc tests of MANOVA and multivariate analysis of covariance. Chapter 7, “Conjoint Analysis,” explains what conjoint analysis does and how it is different from other multivariate techniques. Guidelines of selecting attributes, models, and methods of data collection are presented. Chapter 8, “Cluster Analysis,” studies objectives, roles, and limitations of cluster analysis. Two basic concepts: similarity and distance are discussed. The authors also discuss details of five most popular hierarchical algorithms (singlelinkage, complete-linkage, average-linkage, centroid method, Ward’s method) and three nonhierarchical algorithms (the sequential threshold method, the parallel threshold method, and the optimizing procedure). Profiles of clusters and guidelines for cluster validation are studied as well. Chapter 9, “Multidimensional Scaling and Correspondence Analysis,” introduces two interdependence techniques to display the relationships in the data. The book describes clearly and intuitively the differences between the two techniques and how these two techniques are performed. Chapters 10–12 cover topics in SEM. Chapter 10, “Structural Equation Modeling: An Introduction,” introduces SEM and related concepts such as exogenous, endogenous constructs, and so on, points out the differences between SEM and other multivariate techniques, overviews the decision process of SEM. Chapter 11, “Confirmatory Factor Analysis,” explains the differences between exploratory and confirmatory factor analysis, discusses how to construct, validate, and assess the goodness of fit of a measurement model in SEM by confirmatory factor analysis. Chapter 12, “Testing a Structural Model,” presents some methods of SEM in examining the relationships between latent constructs. The book is an excellent book for people in management and marketing. For the Technometrics audience, this book does not have much flavor of physical, chemical, and engineering sciences. For example, partial least squares, a very popular method in Chemometrics, is discussed but not as detailed as other techniques in the book. Furthermore, due to the amount of materials covered in the book, it might be inappropriate for someone who is new to multivariate analysis.

The Grammar of Graphics

The name of David Graeber had often came across in my conversations with a colleague in the University of Burgos (an anthropologist) when I found this appealing title in the bookshop. The fact that...

The utopia of rules. On technology, stupidity, and the secret joys of bureaucracy

Fact sheets with vivid graphical design and intriguing statistical insights are prevalent for presenting raw data. They help audiences understand data-related facts effectively and make a deep impression. However, designing a fact sheet requires both data and design expertise and is a laborious and time-consuming process. One needs to not only understand the data in depth but also produce intricate graphical representations. To assist in the design process, we present DataShot which, to the best of our knowledge, is the first automated system that creates fact sheets automatically from tabular data. First, we conduct a qualitative analysis of 245 infographic examples to explore general infographic design space at both the sheet and element levels. We identify common infographic structures, sheet layouts, fact types, and visualization styles during the study. Based on these findings, we propose a fact sheet generation pipeline, consisting of fact extraction, fact composition, and presentation synthesis, for the auto-generation workflow. To validate our system, we present use cases with three real-world datasets. We conduct an in-lab user study to understand the usage of our system. Our evaluation results show that DataShot can efficiently generate satisfactory fact sheets to support further customization and data presentation.

DataShot: Automatic Generation of Fact Sheets from Tabular Data

Combining data content with visual embellishments, infographics can effectively deliver messages in an engaging and memorable manner. Various authoring tools have been proposed to facilitate the creation of infographics. However, creating a professional infographic with these authoring tools is still not an easy task, requiring much time and design expertise. Therefore, these tools are generally not attractive to casual users, who are either unwilling to take time to learn the tools or lacking in proper design expertise to create a professional infographic. In this paper, we explore an alternative approach: to automatically generate infographics from natural language statements. We first conducted a preliminary study to explore the design space of infographics. Based on the preliminary study, we built a proof-of-concept system that automatically converts statements about simple proportion-related statistics to a set of infographics with pre-designed styles. Finally, we demonstrated the usability and usefulness of the system through sample results, exhibits, and expert reviews.

Text-to-Viz: Automatic Generation of Infographics from Proportion-Related Natural Language Statements

Data comics for data-driven storytelling are inspired by the visual language of comics and aim to communicate insights in data through visualizations. While comics are widely known, few examples of data comics exist and there has not been any structured analysis nor guidance for their creation. We introduce data-comic design-patterns, each describing a set of panels with a specific narrative purpose, that allow for rapid storyboarding of data comics while showcasing their expressive potential. Our patterns are derived from i) analyzing common patterns in infographics, datavideos, and existing data comics, ii) our experiences creating data comics for different scenarios. Our patterns demonstrate how data comics allow an author to combine the best of both worlds: spatial layout and overview from infographics as well as linearity and narration from videos and presentations.

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Design Patterns for Data Comics

This paper compares the effectiveness of data comics and infographics for data-driven storytelling. While infographics are widely used, comics are increasingly popular for explaining complex and scientific concepts. However, empirical evidence comparing the effectiveness and engagement of infographics, comics and illustrated texts is still lacking. We report on the results of two complementary studies, one in a controlled setting and one in the wild. Our results suggest participants largely prefer data comics in terms of enjoyment, focus, and overall engagement and that comics improve understanding and recall of information in the stories. Our findings help to understand the respective roles of the investigated formats as well as inform the design of more effective data comics and infographics.

/pdf/comparing-effectiveness-and-engagement-of-data-comics-and-9xwtt4gas1.pdf

Comparing Effectiveness and Engagement of Data Comics and Infographics

This paper introduces the concept of 'cheat sheets' for data visualization techniques, a set of concise graphical explanations and textual annotations inspired by infographics, data comics, and cheat sheets in other domains. Cheat sheets aim to address the increasing need for accessible material that supports a wide audience in understanding data visualization techniques, their use, their fallacies and so forth. We have carried out an iterative design process with practitioners, teachers and students of data science and visualization, resulting six types of cheat sheet (anatomy, construction, visual patterns, pitfalls, false-friends and well-known relatives) for six types of visualization, and formats for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

/pdf/cheat-sheets-for-data-visualization-techniques-4huuapizdu.pdf

Cheat Sheets for Data Visualization Techniques

Inspired by data comics, this paper introduces a novel format for reporting controlled studies in the domain of human-computer interaction (HCI). While many studies in HCI follow similar steps in explaining hypotheses, laying out a study design, and reporting results, many of these decisions are buried in blocks of dense scientific text. We propose leveraging data comics as study reports to provide an open and glanceable view of studies by tightly integrating text and images, illustrating design decisions and key insights visually, resulting in visual narratives that can be compelling to non-scientists and researchers alike. Use cases of data comics study reports range from illustrations for non-scientific audiences to graphical abstracts, study summaries, technical talks, textbooks, teaching, blogs, supplementary submission material, and inclusion in scientific articles. This paper provides examples of data comics study reports alongside a graphical repertoire of examples, embedded in a framework of guidelines for creating comics reports which was iterated upon and evaluated through a series of collaborative design sessions.

/pdf/data-comics-for-reporting-controlled-user-studies-in-human-3zus7k6f6j.pdf

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

This paper presents a method for hands-on creation of data comics in a workshop context and includes a description of the results, lessons learned and future improvements. Data comics is a promising format for data-driven storytelling, leveraging the power of data visualization and visual storytelling with comics. However, authoring data comics requires a diverse range of skills that are both creative and analytical. Our workshop is aimed at developing a blue-print for future workshops and reflecting on challenges and potential improvements. Within a 3-week assignment for an illustration class, we ran three 3-hour sessions. Our design was informed by the experiences of previous data-comics workshops. Results show the creative potential of data comics. Challenges to learn from the workshop include the stages to introduce data visualizations and journalistic narratives, the structuring of stories and the method of developing iterations of comic drafts. We close by reflecting on these challenges and how they can inform future improvements and adaptations.

Zezhong Wang

Papers

Design Patterns for Data Comics

Comparing Effectiveness and Engagement of Data Comics and Infographics

Cheat Sheets for Data Visualization Techniques

Data Comics for Reporting Controlled User Studies in Human-Computer Interaction

Teaching Data Visualization and Storytelling with Data Comic Workshops