Part of the Institute of Computer Graphics @ Johannes Kepler University Linz, Austria

Guidance or No Guidance? A Decision Tree Can Help

Teaser

Abstract

Guidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on the user and allowing a positive analysis outcome. However, the boundary between conventional VA approaches and guidance is not sharply defined. As a consequence, framing existing guidance methods is complicated and the development of new approaches is also compromised. In this paper, we try to bring these concepts in order, defining clearer boundaries between guidance and no-guidance. We summarize our findings in form of a decision tree that allows scientists and designers to easily frame their solutions. Finally, we demonstrate the usefulness of our findings by applying our guideline to a set of published approaches.


Citation

Davide Ceneda, Theresia Gschwandtner, Thorsten May, Silvia Miksch, Marc Streit, Christian Tominski
Guidance or No Guidance? A Decision Tree Can Help
EuroVis Workshop on Visual Analytics (EuroVA '18), doi:10.2312/eurova.20181107, 2018.

BibTeX

@article{2018_cbi_industrial-process-management,
    title = {Guidance or No Guidance? A Decision Tree Can Help},
    author = {Davide Ceneda and Theresia Gschwandtner and Thorsten May and Silvia Miksch and Marc Streit and Christian Tominski},
    journal = {EuroVis Workshop on Visual Analytics (EuroVA '18)},
    doi = {10.2312/eurova.20181107},
    year = {2018}
}

Acknowledgements

This work was supported by the Centre for Visual Analytics Science and Technology CVAST, funded by the Austrian Federal Ministry of Science, Research, and Economy in the exceptional Laura Bassi Centres of Excellence initiative (#840262). Further support has been received from the Austrian Science Fund (FWF P27975- NBL), the State of Upper Austria (FFG 851460), and from SoBigData (EU-Grant No. 654024).