Perspectives of Visualization Onboarding and Guidance in VA
Christina Stoiber, Davide Ceneda, Markus Wagner, Victor Schetinger,, Theresia Gschwandtner, Marc Streit, Silvia Miksch, and Wolfgang Aigner

TL;DR
This paper presents a conceptual model for integrating visualization onboarding and guidance in Visual Analytics systems, aiming to improve user assistance and effectiveness for expert users with limited VA experience.
Contribution
It introduces a unified conceptual model based on the Knowledge-Assisted Visual Analytics framework, clarifying the roles and integration of onboarding and guidance in VA.
Findings
Clarifies the differences and commonalities between onboarding and guidance.
Proposes a descriptive model for integrating user assistance in VA tools.
Discusses application of the model across different analysis phases.
Abstract
A typical problem in Visual Analytics 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…
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Taxonomy
TopicsData Visualization and Analytics · Semantic Web and Ontologies · Big Data and Business Intelligence
