Abstract
While most of this book has been aimed at providing general advice, this chapter looks at a set of specific topics. The principles explained in previous chapters are used throughout this one, but the purpose of this chapter is not to give general insights, but instead to provide details on how to visualize time in two specific contexts. The first context is that of large data sets. If large volumes of data are being collected, it is almost certain that there is a temporal component – after all, there is typically a limit on how much data can be collected all at once, and even if you are only collecting a few rows of data every minute, then those intervals add up over the decades. The second topic concerns time events that have strong structural relationships, and where the main goal is to visualize the relationships between the data items rather than the data items themselves. In most of the book our goal has been to discover patterns in the data; this chapter focuses on presenting known patterns so as to learn from them.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Being a fan of Golden Age science fiction makes it painfully clear that any guesses about future technology might lead you to be the subject of much hilarity in the future, as in E. E. “Doc” Smith’s Lensman series, where the title characters rocket around the universe at enormous speeds, plotting their courses with the aid of extremely precise slide rules [101].
- 2.
Another detail to be considered is the color mapping. The scheme used in this figure is a blue-white-red divergent scale, but an alternative would be to use quantiles of counts (such as banding the data into the lower 20%, the next 20%, etc.) This would direct attention to the overall distribution, whereas the mapping shown here highlights extreme values – in this case, those flights with a high cancellation percentage. Which one to use depends on what part of the distribution you are concerned with; quantiling highlights the middle, a simple scale highlights extremes.
- 3.
This paper also provides an example of the way the term “large” is used. The data are described as challenging due to the large number of links – in 1989 over 12,000 links was considered a challenge even for serious computers, as were time data recorded every 5 minutes for a day.
- 4.
This type of chart seems to have been invented first by Karol Adamiecki, who called it a harmonogram, but he didn’t publish it until the 1930s, by which time Henry Gantt had published, among other things, treatises on the social responsibility of business and the chart that now bears his name. More recently, techniques like the PERT (Project Evaluation and Review Technique) chart [35] have been trying to claim, thus far unsuccessfully, the Gantt chart’s project management authority.
- 5.
Not too whimsical, though. Over $25 billion were spent by consumers in the USA on video games alone in 2009, and the company that produces the game in this example is worth about US$6 billion at the time of writing, so managing this industry is not just “for fun.”
- 6.
Note also the difference in clarity between fonts used in the timeline figures in this section. The older, more ornate style is significantly harder to read. Naïvely we might think that the difference is between serif and sanserif fonts, but that is not necessarily true. Practically speaking different fonts are useful for different situations – the ornate font used in the title of Fig. 10.9 is fine, but the ornateness of the labeling hinders understanding. The documentary Helvetica [59] is a fascinating look at typefaces, and in particular the domination of the Helvetica font. Viewing the depth of feeling evidenced by typeface designers over the issue I am hesitant to recommend any particular approach, but Helvetica and its clone, Arial, do work out quite well in many situations, with Verdana another good choice. Arial and Verdana have the advantage of being designed for computer display and are available on both Macintosh and PC systems (but not Linux). Arial is more compact than Verdana, and so if you have to go for a single font for labels on a computer system, it is probably the best current default.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer New York
About this chapter
Cite this chapter
Wills, G. (2010). Topics In Time. In: Visualizing Time. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-0-387-77907-2_10
Download citation
DOI: https://doi.org/10.1007/978-0-387-77907-2_10
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-77906-5
Online ISBN: 978-0-387-77907-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)