Demonstrating Editorial Focus and Learning About Your Data - Data Visualization: A Successful Design Process - page 50

Rather than just throwing everything available at a reader, good visualization
involves showing a degree of editorial care—just because you have some data,
doesn't mean to say you have to use it all. Be selective.
This attitude is necessary for all types of visualization projects. You might think
the idea of telling stories is only relevant for explanatory pieces. That's not the
case. With exploratory designs you still need to demonstrate this editorial focus.
The difference is that with these projects you are not so much telling stories rather
you are making them accessible and discoverable. You still need to frame the
subject matter and define the important dimensions of analysis that will be made
available for manipulation and interrogation. You still need that level of care for
the audience's interpretive experience.
As we'll see later, some of the most effective data visualization designs manage
to create a combination of these functional characteristics, offering a sweet spot of
engaging exploratory features framed within defined story dimensions.
Conversely, if you take a look at a gallery of visualization work and find examples
that you believe are ineffective, they will likely exhibit a weak narrative, an absence
of stories, and a lack of genuine care for the interpretive needs of the audience. This
is a really influential dimension of visualization design.
Preparing and familiarizing yourself with
your data
The following is a quote from Simon Rogers, The Guardian , Facts Are Sacred: The Power
of Data :
"80% perspiration, 10% great idea, 10% output."
Before we get too far down the line of developing and defining our intended stories
and analytical slices, we need to roll up our sleeves and get our hands dirty with the
task of accessing and preparing our data.
Whether you get the data first or shape your desired story dimensions first is mainly
going to be influenced by the context of your project. It is a somewhat "chicken and
egg" situation—which comes first, the data or the focus? You need some focus to
determine what data you need, but you don't know what potential insights exist in
the data until you have it.