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Data characterization for intelligent graphics presentation
Open accessAbstract
An automatic presentation system is an intelligent interface component which receives information from a user or application program and designs a combination of graphics and text that effectively conveys it. It is a facility that assumes the presentation responsibilities for other programs. An important research question has been how information should be specified or described by an application program for it to be presented by an automatic presenter. This paper proposes a taxonomy of information characteristics which would need to be provided to either human or computer designers for them to create presentations reflecting the individual needs of a diverse group of users. The proposed taxonomy of characteristics defines the representational goals for intelligent interfaces which reason about graphical displays.
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Low-Level Components of Analytic Activity in Information Visualization
Amar, R., Eagan, J., & Stasko, J. (2006) · Proceedings of the 2005 IEEE Symposium on Information Visualization (INFOVIS'05) · doi:10.1109/infovis.2005.24 · Cited by 512
Bertrand, A., Viard, T., Belloum, R., Eagan, J. R., & Maxwell, W. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581314 · Cited by 71
A Critical Reflection on Visualization Research: Where Do Decision Making Tasks Hide?
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Metadata
- Authors
- Roth, S. F., & Mattis, J.
- Venue
- Proceedings of the SIGCHI conference on Human factors in computing systems Empowering people - CHI '90
- Publisher
- ACM Press
- Published
- 1990
- Pages
- 193-200
- OpenAlex
- W1976087569
- Cited by
- 201
- References
- 0
- FWCI
- 17.87
- Type
- conference paper
- Language
- en
- Open access
- gold
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- Roth, S. F., & Mattis, J. (1990). Data characterization for intelligent graphics presentation. Proceedings of the SIGCHI conference on Human factors in computing systems Empowering people - CHI '90. https://doi.org/10.1145/97243.97273
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
