NASA Observes Earth Blogs

Robert Simmon of NASA caught this post about the NASA Earth Observatory and was kind enough to pass along some additional information.

Regarding the carbon emissions video:

The U.S. carbon emissions data were taken from the Vulcan Project:

They distribute the data here:

In addition to the animation (which was intended to show the daily cycle and the progress of elevated emissions from east to west each morning), we published a short feature about the project and the dataset, including some graphs that remove the diurnal cycle.

American Carbon is an example of one of our feature articles, which are published every month or so. We try to cover current research, focusing on individual scientists, using narrative techniques. The visualizations tie in closely to the text of the story. I’m the primary visualizer, and I focus on presenting the data as clearly as possible, rather than allowing free-form investigation of data. We also publish daily images (with links to images at the original resolution), imagery of natural hazards emphasizing current events (fires, hurricanes, and dust storms, for example), nasa press releases, a handful of interactive lessons, and the monthly global maps of various parameters. We’re in the finishing stages of a redesign, which will hopefully improve the navigation and site usability.

Also some details about the difficulties of distributing and handling the data:

These sections draw on data from wide and varied sources. The raw data is extremely heterogeneous, formats include: text files, HDF, matlab, camera raw files, GRADS, NetCDF, etc. All in different projections, at different spatial scales, and covering different time periods. Some of them are updated every five minutes, and others are reprocessed periodically. Trying to make the data available—and current—through our site would be overly ambitious. Instead, we focus on a non-expert audience interested in space, technology, and the environment, and link to the original science groups and the relevant data archives. Look in the credit lines of images for links.

Unfortunately the data formats can be very difficult to read. Here’s the main portal for access to NASA Earth Observing System data:

and the direct link to several of the data access interfaces:

And finally, something closer to what was discussed in the earlier post:

With the complexity of the science data, there is a place for an intermediate level of data: processed to a consistent format and readable by common commercial or free software (intervention by a data fairy?). NASA Earth Observations (NEO) is one attempt at solving that problem: global images at 0.1 by 0.1 degrees distributed as lossless-compressed indexed color images and csv files. Obviously there’s work to be done to improve NEO, but we’re getting there. We’re having a workshop this month to develop material for “amateur Earth observers” which will hopefully help us in this area, as well.

This speaks to the audience I tried to address with Visualizing Data in particular (or with Processing in general). There is a group of people who want access to data that’s more low-level than what’s found in a newspaper article, but not as complicated as raw piles of data from measuring instruments that are only decipherable by the scientists who use them.

This is a general theme, not specific to NASA’s data. And I think it’s a little more low-level than requiring that everything be in mashup-friendly XML or JSON feeds, but it seems worthwhile to start thinking about what the guidelines would be for open data distribution. And with such guidelines in place, we can browbeat organizations to play along! Since that would be, uh, a nice way to thank them for making their data available in the first place.

Thursday, July 31, 2008 | acquire, data, feedbag  

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.