Managers and decision makers who know little about data science need a place to start their education and this visualization is a start. I agree with Paul McLeod that it fails to tell the whole story but that in my view is not a failure of visualization, as I think his comment suggests. Systems architects have the same challenge in explaining their craft and illustrating the complex constructs that make up their world. From what I have seen they have developed numerous visual representations that do the job remarkably well. I would challenge data scientists to find ways to transcend the world of algorithms and make their insights more accessible to the unwashed masses.
You know you should have some data science projects on your resume/portfolio to show what you know. The only problem is that although you've taken some intro courses at your school, gone through some MOOC's, and read a few blog posts, when you look to other people's work you think it's out of your league. You want to start working on a data set, yet you're not quite sure what to do with it. At this point, you have some ideas, but you're worried that they're very basic or simplistic. You just want to get your feet wet and learn by doing while proving abilities to a future employer.
Hi Reader, If you're like me, you would like to learn something new every day. I can help with that. This week, we will be talking about data visualizations yet again. Find a comfortable spot, grab a cup of coffee and prepare to do some code. Last week, we talked about how important data visualizations are.
I'm writing a book on data visualization, provisionally titled Data Visualization for Social Science: A practical introduction with R and ggplot2. As part of that process, largely because I've benefited so much myself from the availability of open and widely shared tools for software development, I'm making the draft version of the book available as its own website. It can be found at http://socviz.co. The pitch for the book, more or less, is that it tries to cover best practices in data visualization, for common social science tasks, grounded in good empirical work on the perception of graphics, in a way that is clear, friendly, and provides the code you need to actually make the graphs.
Once again, Popular Science has teamed up with the National Science Foundation to issue a challenge: Can you visualize a scientific idea, concept, or story in an arresting way? If so, submit your work to the 2017 Vizzies! You can enter over on the NSF site. The competition has five categories: photography, illustration, posters and graphics, interactive, and video, which should cover just about every way to communicate science visually. After that, a panel of scientific and visualization experts will choose the winners.