Data life cycle

Summarizing a talk by Xaquín G.V., Natalie Gerhardstein for Delano:

Among González’ takeaways were that, in order to avoid misunderstandings or bias in data visualisation, it helps to be aware of the pitfalls across the lifecycle–from collection through analysis, to the visualisation itself–and, of course, the final story the data is helping to tell. Question, for example, whether correlations being made are legitimate, be transparent and be aware of the visuals aligning with words in the story, he argues.

There are always compromises and possible mistakes upstream before the data comes out as a nicely formatted delimited text file. The more you understand about what happens upstream, the more you can do downstream.