It's exciting times to work with data: more and
more data are becoming available; more people are getting trained in analysis;
better analysis methods provide us with more and better information about our
world. With this came more and trickier problems which require better solutions
for analysis and to supporting analysts. In this talk, I present examples and
interactive interfaces of how data visualization supports analysts along a
range of tasks, including data collection, exploration (http://vistorian.net),
annotation, understanding machine learning (http://playground.tensorflow.org),
and explaining insights findings (http://datacomics.net).
These examples are giving an overview over how to apply data visualization and
which problems visualization research is dealing with. The overarching question
I'd like to discuss is how can we provide better access and training for the
wide variety of visualization techniques, tools, and interfaces?
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