**3. Some design issues**

328 Environmental Monitoring

series analysis, and visual specification of queries was introduced to facilitate the search for

Motion charts, or animated bubble charts, represent another breakthrough in data visualization (the Gapminder website, 2011). The basic display is a 2D bubble chart showing observed pairs of two variables *x* and *y* that have been recorded annually for a set of objects. By highlighting the positions of the bubbles year by year, changes over time can be visualized. Additional information about the investigated objects can be entered into the graphs by colour-coding the bubbles and letting their size vary with some covariate. A Google gadget (the Google website, 2011) has made motion charts available to any user with

The use of animated population pyramids in official statistics (the Australian Bureau of Statistics, 2011) illustrates that almost any static graph in statistics can be animated to visualize changes over time. However, some authors have emphasized that animations are not always superior to static presentations such as a small multiples display (Robertson et al., 2008). Visualization of temporal changes in the size and shape of 2D point clouds represents yet another approach that is particularly suitable for exploring large datasets

Here, we present a flexible two-stage method for making animated bubble charts in Excel®. In the first stage, a macro written in VBA (Visual Basic for Applications) is utilized to identify data tables in a given worksheet and help the user select and organize the inputs to the animation. This macro also creates a suitable bubble-chart template. Thereafter, a

The methods and software solutions we propose are designed to handle fairly large datasets with multiple groups of objects and multiple observations per time stamp and group. Furthermore, it can be noted that the order in which different subsets of data are highlighted can be determined by an arbitrary numerical or string variable. In general, bubble charts are used to visualize relationships between interval variables. However, relationships involving categorical or ordinal variables can also be visualized. In such cases, adding a small amount of noise (jitter) to the original data might be helpful, because it will improve the separation of the data points so that each point is made visible. In addition, the visualization can be extended to high-dimensional time series data by using a macro that first performs principal components analysis and then creates 2D animated

After a brief summary of the general principles of animating bubble charts, and some remarks regarding design issues, we use time series of daily to monthly environmental data to illustrate the power of visual tools to bring out important characteristics of the collected data. Most of our analyses are focused on the occurrence of sudden shifts in the mean or dispersion, and whether or not such shifts can be found in all investigated groups of data. However, the tools presented here are also used to examine temporal trends across seasons and changes along gradients. Moreover, we use a set of multivariate chemical data on olive oils to illustrate how animated score charts can highlight differences between geographical

After presenting a set of useful displays and animation options, we resume our discussion of factors that influence the visual impression of static and animated charts, and we also consider how to achieve a good balance between the information content of a display and perceptual capacity limits. In addition, we address some technical aspects of using

spreadsheets with tens of thousands of observations.

collection of other VBA macros is employed to produce the animation.

interesting features of time series data (Hochheiser et al., 2003).

a good Internet connection.

(Landesberger et al., 2009).

score charts.

regions.

A user-friendly implementation of animated bubble charts requires a good balance between flexibility and standardization. The selection of data and the design of the bubble charts should be flexible, whereas efficient updating of spreadsheets and graphs is greatly facilitated if the data tables have a standardized design. This favours two-stage procedures in which a set of user forms first help the user organize the data in a standardized manner and create a suitable graph template; thereafter, the animation can be run and controlled with buttons and scroll bars.

We created a VBA macro that initially determines the position and size of the data tables that are to be visualized, and then utilizes list boxes to select up to five variables for an animated bubble chart. The first variable, which is required and may represent a time stamp, is used to control the highlighting of different subsets of data. Variables two and three, which are also required, represent the *x* and *y* variables in a bubble chart. Variable four, which is optional, can be used to partition the set of bubbles into different groups. Finally, another optional variable can be used to size code the bubbles.

The macro that prepares for the animation can also allow the user to select a suitable step length (time step) for the animation and a desired range of animation records (time span). Furthermore, the preparations include automatic scaling of the *x*- and *y*-axes of the bubble chart and selection of marker types. The applicability of animated bubble charts can be further increased by performing an optional standardization of the *x* and *y* variables to mean zero and variance one, and by calculating the first two principal components of a userdefined set of variables. In the latter case, high-dimensional data can be scrutinized by creating animated 2D score charts.
