Perspectives of visualization onboarding and guidance in VA

A typical problem in Visual Analytics(VA)is that users are highly trained experts in their application domains,but have mostly no experience in using VA systems.Thus,users often have difficulties interpreting and working with visual representations.To overcome these problems,user assistance can be incorporated into VA systems to guide experts through the analysis while closing their knowledge gaps.Different types of user assistance can be applied to extend the power of VA,enhance the user’s experience,and broaden the audience for VA.Although different approaches to visualization onboarding and guidance in VA already exist,there is a lack of research on how to design and integrate them in effective and efficient ways.Therefore,we aim at putting together the pieces of the mosaic to form a coherent whole.Based on the Knowledge-Assisted Visual Analytics model,we contribute a conceptual model of user assistance for VA by integrating the process of visualization onboarding and guidance as the two main approaches in this direction.As a result,we clarify and discuss the commonalities and differences between visualization onboarding and guidance,and discuss how they benefit from the integration of knowledge extraction and exploration.Finally,we discuss our descriptive model by applying it to VA tools integrating visualization onboarding and guidance,and showing how they should be utilized in different phases of the analysis in order to be effective and accepted by the user.

Comparative evaluations of visualization onboarding methods

Comprehending and exploring large and complex data is becoming increasingly important for a diverse population of users in a wide range of application domains.Visualization has proven to be well-suited in supporting this endeavor by tapping into the power of human visual perception.However,non-experts in the field of visual data analysis often have problems with correctly reading and interpreting information from visualization idioms that are new to them.To support novices in learning how to use new digital technologies,the concept of onboarding has been successfully applied in other fields and first approaches also exist in the visualization domain.However,empirical evidence on the effectiveness of such approaches is scarce.Therefore,we conducted three studies with Amazon Mechanical Turk(MTurk)workers and students investigating visualization onboarding at different levels:(1)Firstly,we explored the effect of visualization onboarding,using an interactive step-by-step guide,on user performance for four increasingly complex visualization techniques with time-oriented data:a bar chart,a horizon graph,a change matrix,and a parallel coordinates plot.We performed a between-subject experiment with 596 participants in total.The results showed that there are no significant differences between the answer correctness of the questions with and without onboarding.Particularly,participants commented that for highly familiar visualization types no onboarding is needed.However,for the most unfamiliar visualization type—the parallel coordinates plot—performance improvement can be observed with onboarding.(2)Thus,we performed a second study with MTurk workers and the parallel coordinates plot to assess if there is a difference in user performances on different visualization onboarding types:step-by-step,scrollytelling tutorial,and video tutorial.The study revealed that the video tutorial was ranked as the most positive on average,based on a sentiment analysis,followed by the scrollytelling tutorial and the interactive step-by-step guide.(3)As videos are a traditional method to support users,we decided to use the scrollytelling approach as a less prevalent way and explore it in more detail.Therefore,for our third study,we gathered data towards users’experience in using the in-situ scrollytelling for the VA tool Netflower.The results of the evaluation with students showed that they preferred scrollytelling over the tutorial integrated in the Netflower landing page.Moreover,for all three studies we explored the effect of task difficulty.In summary,the in-situ scrollytelling approach works well for integrating onboarding in a visualization tool.Additionally,a video tutorial can help to introduce interaction techniques of visualization.

VisAhoi:Towards a library to generate and integrate visualization onboarding using high-level visualization grammars

Visualization onboarding supports users in reading,interpreting,and extracting information from visual data representations.General-purpose onboarding tools and libraries are applicable for explaining a wide range of graphical user interfaces but cannot handle specific visualization requirements.This paper describes a first step towards developing an onboarding library called VisAhoi,which is easy to integrate,extend,semi-automate,reuse,and customize.VisAhoi supports the creation of onboarding elements for different visualization types and datasets.We demonstrate how to extract and describe onboarding instructions using three well-known high-level descriptive visualization grammars—Vega-Lite,Plotly.js,and ECharts.We show the applicability of our library by performing two usage scenarios that describe the integration of VisAhoi into a VA tool for the analysis of high-throughput screening(HTS)data and,second,into a Flourish template to provide an authoring tool for data journalists for a treemap visualization.We provide a supplementary website(https://datavisyn.github.io/visAhoi/)that demonstrates the applicability of VisAhoi to various visualizations,including a bar chart,a horizon graph,a change matrix/heatmap,a scatterplot,and a treemap visualization.