Project: Gender in Conference Talks #AAS225

For anyone who will be attending the upcoming AAS 225 meeting next week in Seattle, WA, I want to give you a heads up to help participate in a study I will be conducting!

This is a follow-up to last year's pilot study I organized on gender in astronomy talks. I asked conference attendees to record the gender of the speakers and the questioners for every talk they attended, hoping to answer simple questions like: Do women get asked more questions by men or women? This unique and ongoing study is the first of its kind for Astronomy (that I'm aware of), and will hopefully help determine best practices for conducting meetings and talks to promote inclusiveness and interaction by all.

Our report from AAS 223 is here!

The study was also conducted at NAM 2014, and they wrote a very fine report about it here!

This year I'll be gathering data again using a simple web form that should work on computer/iPhone/etc. The goal is to make adding data painless while listening to the talks. We hope to get data on 100% of the talks this year, and will need help from as many people as possible.

Please help spread the word about the study, and contact me with questions/comments via Twitter or my website.

See you at #AAS225!

Survey is here!

Radio Maps II: Nielsen BDS Stations

In part I of this series of posts I made this neat looking map of all FM radio station transmitter coverage in the US:

This is basically a population density map of course, but the data is intriguing for many reasons and the subject matter of listening to the radio on road trips is full of nostalgia.

Once I started making this map I immediately knew that I had to do a few studies on this fascinating dataset! My next goal was to start grouping the stations by genre information. As a first example of this, I am looking at the ~1600 stations that the Nielsen company monitors (excluding AM and Canadian stations, so actually closer to 1200 stations). Here I'm matching/joining the FCC's transmission coverage data to the Nielsen BDS stations using their call sign (e.g. KUOW). I then grouped the stations by genre/format, and used the Python Basemap package (very sloppily) to draw the geographies

Here's the first image in the set:

Your first reaction might be: is this just another population density map?

Answer: no. The Nielsen BDS stations listen to targeted music/programming in certain markets. They don't listen to every Adult Contemporary station throughout the US, only selected stations in key markets. How these markets are determined is beyond me, and probably a matter of trade secrets or voodoo, I'd suppose...

So what we have in these maps is more like the geographic regions where each radio format/genre is considered important, or are good predictors of sales/popularity.

All caveats aside, there are some very interesting trends in the geographies vs genre, which largely track racial and socioeconomic distributions.

Here's an album of all the images (direct link here incase the widget isn't working well)



For my next post on the distribution of radio stations in the US, I'm working to compile a larger database of most every station with a known format. So far I'm aggregating tables from wikipedia, but if you have a line on a more complete list drop me a line! Then I'll be able to discuss the actual geography of musical tastes in the US.

The long term goal for this ongoing project is called RadioTrip, where users could get map directions and radio suggestions along the way based on musical taste. If you want to help with this project, let me know or ping me on GitHub!

Volcanoes of the World

Here's a fun figure I made: every volcano on the planet, colored by every known eruption.

(Click for full size)

This data comes courtesy of the Smithsonian Institute's Global Volcanism Program. This dataset includes 10734 known eruptions from 1562 individual volcanoes, going back about 12000 years!

Of course the data are not complete throughout history, but should be quite robust for modern times. For reference, there are 176 entries for eruptions since 2010!!

Our planet is incredible.


update: Some people felt I was under-selling the volcanism of Iceland, and also some folks don't like the Hammer-Aitoff projection I used... so here's another version using a more Euro-centric view and a Robinson map projection:

(Click for full size)

The Rainbow is not Dead

What I have to say may shock some of you: the rainbow color map isn't dead, and it shouldn't be.

Boom. Let the rage begin!

It might seem surprising for me to say that, since I've been a huge advocate of the cubehelix color map on this site (and IRL). Some of my friends have also penned strongly worded comments against rainbow (aka jet). I've been known to wax on about it too. There have also been widely read critics of this color map recently, which pushed me to write my own (shudder) defense of the rainbow.

Most of the criticism is well founded, and falls along a few (excellent) lines of reasoning:

1. It doesn't desaturate to black/white sensibly
2. The color order is not universally understood
3. It is hard to make out fine details, and can artificially exaggerate others
4. It includes colors which are hard to see (e.g. cyan, yellow)

I argue that's not the whole story....

The tl;dr answer: some data is categorical not continuous, and some continuous data needs certain features highlighted. Always choose colors for a reason.

Let's break it down... here's a figure that aesthetically irritates me (I'm nitpicking on the astroml figures here because they are damned excellent). People use this kind of figure as an example of good plotting style and nice visualization methods. It is also used it as an example of bad color choices and weird visual artifacts.

This figure is good and bad. Specifically, the left panel is probably bad, the right seems good.

(SDSS surface gravity versus temperature for stars. From here)