Paper: Blaze: Building A Foundation for Array-Oriented Computing in Python (Mark Wiebe)

Skeleton up.  Should be workable soon.

cc @mwiebe 
**General remarks about the introduction**

What is the *data analytics ecosystem* and why do I care about it?  The first paragraph is a little heavy on jargon, it is difficult for me to extract the impact to library challenges in data science that users of varying level of expertise have.

In delivering a rather striking example, the second paragraph uses the term *backend*, a common vernacular in several computing communities for *implementation*.  Although backend is commonly used within the computational Python community, I think this paragraph would be a lot stronger if it was described in the (more) common parlance of *interface* and *implementation*.  

> Standard interfaces allow library developers to evolve rapidly without the drag of a hostage user community.

The first paragraph can be summarized as: "The data ecosystem is growing rapidly with expert and novice users."  The second paragraph: "Standard interfaces improve adoption and make working with complex systems easier"  The third, "standard interfaces help users and developers."

The third paragraph seems out of place in the introduction.  Consider stronger topics in the paragraphs, e.g., "interfaces help users because...", "interfaces help developers because..."