Manuel Lima, who is behind the Visual Complexity project, recently posted an Information Visualization Manifesto, which has created quite some stir in the info vis blogosphere. The manifesto is a list of ten principles or guidelines that he recommends info vis practitioner’s should follow. And while his proposed guidelines overall have resonated well in the community, his attempt to separate information visualization from what he calls “information art” has lead to a heated debate.
Manuel has now followed up with a second post that summarizes the observations he made discussing the manifesto with readers of his blog.
In support of the information visualization manifesto, Robert Kosara over at EagerEyes has written about the “pretty picture stigma”. In his post he proposes to use the term “visual analysis” instead of “visualization” to emphasize that the key aspect of data visualization is actually analysis (and not pretty pictures), which might not be so obvious to everyone. He adds that “[v]isual analysis is difficult” and everyone who has ever tried to come up with a way to visually represent complex biological data will confirm this.
All three posts provide plenty of thoughtful insight into the consequences of the increasingly blurry boundaries between information visualization research, information design and “information art”. Manuel and Robert also hint at some of the reasons why in bioinformatics we are still struggling with visualization, while there are new and fancy visualizations popping up all over web almost on a daily basis: it’s all about the data.
PS. I realize that this discussion might be a bit beyond the casual info vis practitioner’s interests, but it’s worthwhile to follow this debate to put things into perspective.