  With the rise of the open data movement a lot of statistical data has been
made publicly available by governments, statistical offices and other
organizations. First efforts to visualize are made by the data providers
themselves. Data aggregators go a step beyond: they collect data from different
open data repositories and make them comparable by providing data sets from
different providers and showing different statistics in the same chart. Another
approach is to visualize two different indicators in a scatter plot or on a
map. The integration of several data sets in one graph can have several
drawbacks: different scales and units are mixed, the graph gets visually
cluttered and one cannot easily distinguish between different indicators. Our
approach marks a combination of (1) the integration of live data from different
data sources, (2) presenting different indicators in coordinated visualizations
and (3) allows adding user visualizations to enrich official statistics with
personal data. Each indicator gets its own visualization, which fits best for
the individual indicator in case of visualization type, scale, unit etc. The
different visualizations are linked, so that related items can easily be
identified by using mouse over effects on data items.
