Writing

Renting Big Data

logo_aws.gifBack in December (or maybe even November… sorry, digging out my inbox this morning) Amazon announced the availability of public data sets for their Elastic Compute Cloud platform:

Previously, large data sets such as the mapping of the Human Genome and the US Census data required hours or days to locate, download, customize, and analyze. Now, anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. For example, users can produce or use prebuilt server images with tools and applications to analyze the data sets. By hosting this important and useful data with cost-efficient services such as Amazon EC2, AWS hopes to provide researchers across a variety of disciplines and industries with tools to enable more innovation, more quickly.

The current lists includes ENSEMBL (550 GB), GenBank (250 GB), various collections from the US Census (about 500 GB), and a handful of others (with more promised). I’m excited about the items under the “Economy” heading, since lots of that information has to date been difficult to track down in one place and in a single format.

While it may be possible to download these as raw files from FTP servers from their original sources, it’s already set up for you, rather than running rsync or ncftp for twenty-four hours, then spending an afternoon setting up a Linux server with MySQL and lots of big disk space, and dealing with various issues regarding versions of Apache, MySQL, PHP, different Perl modules to be installed, permissions to be fixed, etc. etc. (Can you tell the pain is real?)

As I understand it, you start with a frozen version of the database, then import that into your own workspace on AWS, and pay only for the CPU time, storage, and bandwidth that you actually use. Pricing details are here, but wear boots — there’s a lotta cloud marketingspeak to wade through.

(Thanks to Andrew Otwell for the nudge.)

Sunday, January 25, 2009 | acquire, data, goinuptotheserverinthesky  
Book

Visualizing Data Book CoverVisualizing Data is my book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.

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