Skip to main content
Top

2012 | OriginalPaper | Chapter

9. Interactivity

Author : Graham Wills

Published in: Visualizing Time

Publisher: Springer New York

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Interactivity is a fundamental property of items in the real world. We expect to be able to turn things on, move them around, change locations, or at the very least shift our viewpoint so as to see them in a different way. We color objects, resize and reshape them, and interact with them in many ways. Exploration via interactivity is a basic children’s activity, leading to understanding. It is a key way of learning we encourage in children and is no less valuable for adults. An old Chinese adage, often attributed to Confucius, states “I hear and I forget. I see and I remember. I do and I understand.” That is the basic premise of interactivity. It leverages the way we achieve understanding in the physical world, building on the visual (“I see and I remember”) and enforcing it with actions that allow us to manipulate displays and so improve our knowledge of the data that are being visualized (“I do and I understand”). Interactive data visualizations allow users to see pop-ups and tool tips; rotate, pan, and zoom in on plots; selectively show details in some areas while maintaining an overall view of the context; drill down into subareas of the data space; manipulate parameters such as degree of smoothing; select parts of one view and see corresponding items highlighted in another view; and dynamically filter data with controls or via direct manipulation.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Footnotes
1
Exploration is characterized as being fast, immersive, and data-focused. Presentation is characterized as being precise, reflective, and view-focused.
 
2
There have been many attempts to automatically choose good bin widths for histograms. Scott [97] gives a formula that minimizes the mean square error between an underlying distribution and the visual representation. If σ is the standard deviation and N the sample size, then the width, W, is given by
$$W = 3.49\sigma {N}^{-1/3}.$$
Freedman and Diaconis suggest replacing the use of the standard deviation with the interquartile range – the distance covered by the “middle half” of the data or, more formally, the distance between the first and third quartile. This is somewhat more robust and gives the folowing formula:
$$W = 2\;IQR\;{N}^{-1/3}.$$
However, even this is not a perfect solution. If data are regular, as often happens in time series data, it is inappropriate to choose a bin width that is not a multiple of the natural spacing of the data. For example, if dates are always in days, a bin width of 1.7 days is always going to be a poor choice. For regular data, therefore, it is recommended that the optimal bin width be that integer multiple of the data granularity that is closest to Freedman and Diaconis’s formula. If you want to do a truly stellar job, then you should also check the units of your data and bias toward reasonable bins based on that, as suggested in Sect. 8.3.2).
 
3
If we actually set r = 0, then we get a flat line in the center as the transform then becomes y = x 0, or y = 1, so this graph was produced by setting r = 0. 000001. Mathematically this function is extremely close to the log function, so for practical purposes, choosing this value of r is the same as choosing a log transformation.
 
4
One potentially useful application would be if we transformed the categorical variable by aggregating all infrequent values into a single category, so, as an example for the email data, we might facet by data sender and have only the most frequent K senders retained. Other emails might be filtered out of the data or be given a single sender value like other. In this case, putting K under interactive control would be a useful exploratory technique.
 
5
Since this chart shows time series for each variable by each month, a single row of data is shown in all four lines, which is why the selection is duplicated in each line.
 
6
For spatial data the window width can be used to define a geographic region, typically a disk, that can be moved over a map to highlight data that lie in that region. An early example of such an interactive geographic exploration system is given in [50].
 
Metadata
Title
Interactivity
Author
Graham Wills
Copyright Year
2012
Publisher
Springer New York
DOI
https://doi.org/10.1007/978-0-387-77907-2_9

Premium Partner