Present / visualize aggregated data for years I have yearly data for the import of fish products to Portugal (years 2000 to 2011) per country. There are some trends that I would like to visualize, for example some countries drop out and enter in the top 5 as exporters.
Now I'm not really sure how I can do it in a non-confusing way that highlights the changes but does not miscommunicate the statistics and is clean. IMO in the line chart (apart from having too much content) changes are more apparent than, for example, in pie charts (only two datasets shown). But is it correct to visualize aggregated data in line charts (or may I falsely communicate that the data is connected)?
Line chart

Pie charts

 A: You can definitely use line charts to communicate change. You should not use pie charts. As the great John Tukey said "there is no data that can be displayed in a pie chart that cannot better be displayed in some other type of chart". 
Line charts do seem to me to imply connectedness - but your data are moving averages! They are connected. However, you might prefer to use individual years and a different smoother (e.g. loess). 
If you think there are too many lines on the graph, I suggest separating them by some factor, either, as @Andreas suggests, geographic region or by initial level.
A: You're on the right path with the line chart (as Peter Flom mentioned, AVOID PIE CHARTS, especially comparing two of them).  As for the line chart, consider the message you're trying to convey and use the chart's formatting to reinforce the message.  
Here's an example where perhaps you want to emphasize the strongest importer at the beginning period in comparison with the strongest at the end.

By using pre-attentive attributes like color, you can direct the viewers attention to the information you want them to focus on.  Include a more descriptive title that summarizes your message and the line chart can really focus your reader.  All the other information is still present, so you don't lose context.
A: Consider the following:


*

*Using bar charts to group together three year averages.

*Using the 'ggplot2' package in R with the 'facet_wrap' command to produce separate graphs for each geographic region. This will help to make the graphs easier to read by removing clutter.

