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The Grand Tour: A Tool for Viewing Multidimensional Data
Abstract
The grand tour is a method for viewing multivariate statistical data via orthogonal projections onto a sequence of two-dimensional subspaces. The sequence of subspaces is chosen so that it is dense in the set of all two-dimensional subspaces. Desirable properties of such sequences of subspaces are considered, and several specific types of sequences are tested for rapidity of becoming dense. Tabulations are provided of the minimum length of a grand tour sequence necessary to achieve various degrees of denseness in dimensions up to 20.
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Cited by
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Diaconis, P. (1988) · doi:10.1214/lnms/1215467407 · Cited by 1,381
Spatial data analysis: theory and practice
(2004) · Choice Reviews Online · doi:10.5860/choice.41-3486 · Cited by 965
Hyperdimensional Data Analysis Using Parallel Coordinates
Wegman, E. J. (1990) · Journal of the American Statistical Association · doi:10.1080/01621459.1990.10474926 · Cited by 688
Parallel coordinates: a tool for visualizing multi-dimensional geometry
Inselberg, A., & Dimsdale, B. (2002) · Proceedings of the First IEEE Conference on Visualization: Visualization `90 · doi:10.1109/visual.1990.146402 · Cited by 574
The early origins and development of the scatterplot
Friendly, M., & Denis, D. (2005) · Journal of the History of the Behavioral Sciences · doi:10.1002/jhbs.20078 · Cited by 184
Metadata
- Authors
- Asimov, D.
- Venue
- SIAM Journal on Scientific and Statistical Computing
- Published
- 1985-01
- Volume
- 6
- Issue
- 1
- Pages
- 128-143
- ISSN
- 0196-5204 (ISSN-L)
- 2168-3417
- OpenAlex
- W1978841917
- Cited by
- 659
- References
- 0
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The Grand Tour: A Tool for Viewing Multidimensional Data. https://app.cochat.ai/papers/10.1137/0906011
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- Asimov, D. (1985). The Grand Tour: A Tool for Viewing Multidimensional Data. SIAM Journal on Scientific and Statistical Computing. https://doi.org/10.1137/0906011
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
