Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection
- Submitting institution
-
Swansea University / Prifysgol Abertawe
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 18118
- Type
- D - Journal article
- DOI
-
10.1109/TVCG.2014.2346428
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 2261
- Volume
- 20
- Issue
- 12
- ISSN
- 1941-0506
- Open access status
- Out of scope for open access requirements
- Month of publication
- November
- Year of publication
- 2014
- URL
-
http://cs.swansea.ac.uk/~csmark/PDFS/2014_infovis_order_of_magnitude_markers.pdf
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- 10
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- A large spread of orders of magnitude within data poses a well-known problem for charts for which logarithmic scales are a widely used solution that then leads to problems estimating relative scale. We solve this with a completely new visual representation. We utilise task-based analysis in a high-quality user study to discover the impact of our new depiction on accuracy and speed for trend analysis, number identification, comparison, and outlier detection tasks. This paper challenges existing perceptions of charting and opens a new area for future research.
IEEE TVCG is the top journal for visualization research, especially the conference issue.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -