Chapter 8 Next-Generation Cyberinfrastructures

So far in this book we have covered many components of biomedical data management and analysis. Of course, as you have already certainly realized, the neat separation of topics into chapters doesn’t hold in real life. In research, clinical, and administrative settings, they overlap and interrelate in ways that are at once messy and fascinating. There are countless such scenarios—far, far more than we can cover in this book. But in this last chapter we share one example that we hope is rich and compelling.

Larger research institutions, in particular, find themselves dealing with many, if not all, of the issues covered in this book: genomic analysis, data management, data storage, networking, infrastructure, and data science. As a way of synthesizing the various strands and themes of this book and providing a specific example, we share the story of Arizona State University (ASU). We detail how we have chosen to meet our community’s data and compute needs in ways that we hope will continue to put us on good footing and foster first-rate research. ASU offers a valuable example because it is a very large research institution, with over 90,000 enrolled students and over 3,000 faculty. And to sing our own praises, we were honored in the 2016 university ratings by U.S. News & World Report, where we ranked No. 1 among the Most Innovative Schools in America. It is also, of course, best to write about what you know.

In 2014 I accepted the ...

Get Strategies in Biomedical Data Science now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.