Visualization Onboarding Grounded in Educational Theories

VisualizationOnboarding Teaser

Abstract

The aim of visualization is to support people in dealing with large and complex information structures, to make these structures more comprehensible, facilitate exploration, and enable knowledge discovery. However, users often have problems reading and interpreting data from visualizations, in particular when they experience them for the first time. A lack of visualization literacy, i.e., knowledge in terms of domain, data, visual encoding, interaction, and also analytical methods can be observed. To support users in learning how to use new digital technologies, the concept of onboarding has been successfully applied in other domains. However, it has not received much attention from the visualization community so far. This chapter aims to fill this gap by defining the concept and systematically laying out the design space of onboarding in the context of visualization as a descriptive design space. On this basis, we present a survey of approaches from the academic community as well as from commercial products, especially surveying educational theories that inform the onboarding strategies. Additionally, we derived design considerations based on previous publications and present some guidelines for the design of visualization onboarding concepts.


Citation

Christina Stoiber, Markus Wagner, Florian Grassinger, Margit Pohl, Holger Stitz, Marc Streit, Benjamin Potzmann, Wolfgang Aigner
Visualization Onboarding Grounded in Educational Theories
Springer Nature (to appear), doi:10.48550/arXiv.2203.11134, 2022.

BibTeX

@article{,
    title = {Visualization Onboarding Grounded in Educational Theories},
    author = {Christina Stoiber and Markus Wagner and Florian Grassinger and Margit Pohl and Holger Stitz and Marc Streit and Benjamin Potzmann and Wolfgang Aigner},
    journal = {Springer Nature (to appear)},
    publisher = {Springer (ArXiv Preprint)},
    doi = {10.48550/arXiv.2203.11134},
    url = {https://doi.org/10.48550/arXiv.2203.11134},
    month = {March},
    year = {2022}
}

Acknowledgements

This work was funded by the Austrian Science Fund as part of the VisOnFire project (FWF P27975-NBL), the Austrian Ministry for Transport, Innovation and Technology (BMVIT) under the ICT of the Future program via the SEVA project (no. 874018), as well as the FFG, Contract No. 854184: “Pro2Future”, which is funded within the Austrian COMET Program Competence Centers for Excellent Technologies under the auspices of the Austrian Federal Ministry for Transport, Innovation and Technology, the Austrian Federal Ministry for Digital and Economic Aairs and of the Provinces of Upper Austria and Styria. COMET is managed by the Austrian Research Promotion Agency FFG.