Smile Novae

No comments:




While looking through some research papers and reading about binary stars this morning, I happened across a graphic that blew my mind. I was reading "BoB" to refresh my memory on some terminology, when I saw this smiling supernova starring back at me. Here he is, excerpted from the actual research paper:
from Fig. 1 of Iben & Tutukov (1984).
Copyright belongs to the Astrophysical Journal.

The UW Libraries: Part 1

No comments:
UW's Suzzallo Library (image taken from here)
In college at UW I had a part time job in the library for about a year. Like many people I worked part time through most of college. I've heard it said that part time employment, ideally on campus, improves academic performance. This was certainly true in my case.

Working at the library was an ideal job for me. The hours were flexible around classes, I could wander around interesting parts of the collection I would have never otherwise seen, and I could steal a nap on the 4th floor when on opening shift.


I've reflected a lot on my college experience recently, as many people naturally do. I met my wife then, I changed from pursuing an engineering career to academia and astronomy, I did a lot of growing up. (Incidentally, I didn't learn how to become a good student until I was enrolled in a Masters program) None of these changes in my life were expected when I left my rural high school for the big city. I didn't have a good idea of what University would really be about.

I certainly never expected to become an advocate for libraries, nor becoming a member of a couple library advisory committees at UW in grad school. In high school and college I was an avid non-reader. "Books? I never touch the stuff." As I've grown to be part of the academic sphere, the critical role of libraries becomes more clear. And I even read books now, so it goes.

[\end boring backstory]

As technology sweeps through our culture, bringing iPods, Kindles, and Netflix, "traditional" media has struggled to survive the changing climate. Libraries have weathered this storm largely by adapting their scope, becoming a palace of wifi rather than of dusty texts. Thoreau, Feynman, and Kant are all still there, but you'll more likely encounter them in a PDF. Someday (soon I hope) publishers, Google, and libraries will get this "digital library" thing set up right...

This blog is nominally about science, data, and musing on the world around me. That means it's time for some library statistics! It just so happens that libraries, which are run by smart people, have been keeping statistics on their usage for a long time (e.g. see the Association of Research Libraries). UW's libraries keep significant data, and I saw a great talk by Steve Hiller a few months ago on the subject. The data driven goal of this first library post will be to look at the usage trends of the UW library system, to gauge the importance of this major university facility.

Fig 1. Average of autumn, winter, spring enrollment. Data from the UW Factbook.
First, consider the enrollment trend at UW for the last two decades (above). The UW campus has grown by ~25% since 1992. If we assume that the fraction of students checking out books stays the same, then the libraries should have received an increase in attendance.

Fig 2. Monthly gate counts of patrons for all UW Seattle libraries as a function of time.
We can see in Figure 2, however, that over the last 10 years the monthly gate counts (warm bodies walking through the door) have been nearly constant. This monthly data has strong annual structure, which I'll highlight at the end. Since enrollment has been increasing, the fraction of people visiting the libraries is either decreasing, or the number of people who can visit the libraries has "saturated" (i.e. the library is at patron capacity). My intuition is the former. The flat trend in library patrons over time presents a clear message: people still go to the libraries.

Fig 3. Total number of items used per academic quarter, which includes checkouts,
renewals, reserved, and re-shelved in-library items.
In Figure 3 I'm showing the number of items used per quarter at all UW Seattle library branches. This includes items checked out, reserves, renewals of items already checked out, and books/items used in the library but not checked out.  There is a slight decrease over the last 6 years in material usage, but the trend is slight.

Fig 4.  Number of checkouts per academic quarter.

However, Figure 4 tells a somewhat different story. Just tracking the # of checked out items per quarter shows distinct decrease. This decline accounts for most of the net decrease in item usage seen in Figure 3. If you combine this decline with the rapidly increasing enrollment, one conclusion becomes clear: People aren't checking out books. Not at the rates of years past, at least.

Fig 5. Monthly gate counts of patrons at all UW Seattle libraries from 2002 to 2010,
folded over the academic year.

Finally we come back to the monthly gate counts of patrons walking through the library doors in Figure 5. As I mentioned above, the volume of patrons in the library has remained very steady. When we show these numbers as a function of month, placing each year on top of the other, an awesome and repeating pattern emerges (Fig 5). This subtly tells the story of how students use the libraries, how they continue to view them as critical to their academic success.

In Autumn quarter, which typically starts around the last week of September, students flock to the libraries. The patronage that month is around 120% of the average! Year after year this is seen. Eager learners coming to the place they know will fill them with knowledge and inspiration.

By the 2nd month of Autumn quarter they have "figured it out". Thanksgiving holiday sends students away, often for a week, but in general library use is strong. December numbers plummet. Winter holiday takes 2 weeks, and many students finish with classes in early Dec.

The rest of the year reads off like a coarse academic calendar. Spring break in March. Graduation in June. Summer term in July/August.  Library usage peaks when students are hopeful or have deadlines, and drops over holidays.

That's nearly all I have to say about these data (right now). To get a full sense of what the library is "good for" these days we'd need to see data on electronic usage and journal subscriptions/use, not included here and probably harder to quantify.  I believe there is a clear message here: the library continues to be a hugely used resource on our campus, but the use of books decreases steadily. The library must therefore transition to becoming a more general hub for learning. From my meetings/conversations with admin in the library I can tell you that they know this, and are scrambling to redefine their scope. I mourn the loss of books in our every day lives. Small used book stores used to be found everywhere around UW, now I can only think of 1 within walking distance (Magus, and it is awesome). I sincerely hope, however, that the decline of paper book use does not come hand in hand with the decline in educational quality of our university... you're welcome to wildly speculate to that end.

Coffee: Two Minutes from Anywhere

2 comments:
Be sure to subscribe for updates on this and all my other data analysis projects!

I live in Seattle, the self proclaimed "coffee capitol" of the USA. We have a Starbucks on every corner downtown, independent cafes all over, and even some Starbucks incognito as indie coffee stores. It's a wonderfully caffeinated culture we're brewing out here.

A long standing joke among my friends at the University of Washington (UW): we drink so much coffee that we put a cafe in nearly every building on campus. This isn't quite true, of course, but we do have many!

While driving home from school today it occurred to me to consider the joke in a different direction: how far on UW's campus can you get from a cafe? Are you ever more than 2 minutes away from a coffee stand?

So I set about finding the answer!

Water Water

1 comment:
I found a link while browsing reddit this afternoon (from r/dataisbeautiful) that pointed to a community data visualization challenge.  The source for the data was a "Global Water Experiment", which provided some basic measurements of water characteristics, such as pH.

Though the data challenge had passed its deadline by a couple weeks, I was still intrigued, and so I used a couple free hours while some code was running on my work machine to play with this "Global Experiment".

Aside: It is becoming clear to me that I need to learn some new data visualization software, and I haven't been very impressed with most graphics I've seen from python. R sounds like a cool option, it's free and widely used... we'll see what I get in to.


I downloaded the .xls file, and while looking through the data on pH levels a question popped in to my head!


Question: does the "financial prowess" of a country correlate with the quality of its drinking water as tracked by pH levels?


This really reminded me of the (now famous) TED talk by Hans Roling, and his cute data visualization that everyone gushed over a few years ago - and it really is a cool talk, btw.  Some quick searching online suggests that this sort of effect has been investigated before, but results have been largely inconclusive, or consistent with no correlation.

The challenge data provided me with over 2000 pH measurements from almost a hundred countries, though the sampling seemed sporadic between countries. I had to spend some time "cleaning" the data file by making names of countries uniform (e.g. USA became United States) and getting rid of non-standard characters.

The financial numbers came from Gross Domestic Product (GDP) data, provided courtesy of the CIA as it so happened!

So armed with my two sources of data, I set about the ever-fun task of string matching. It's somewhat of a clunky operation in IDL, and I always recommend people try a few things when doing this:

  1. trim any leading/trailing spaces using STRTRIM(inputstring,2)
  2. convert everything to lower case using STRLOWCASE(inputstring)
  3. if things vary too much, you can try matching over only part of the string using the vector functionality of STRMID()
I matched the GDP and pH data, and then selected only the fresh water samples. I was a bit hasty with the matching, and probably threw out by accident some of the pH sampling. I also missed some country name matching, no doubt.

For each country with GDP and pH data, I measured the mean (average) and standard deviation of the pH samples, with Std Dev only calculated for countries with 2 or more samples. The immediate red flag that should go up in your mind (or certainly did for me) was: don't some countries have drastically different water environments that are being tested? Absolutely! As I mentioned above, this study didn't seem to guarantee any certain degree of accuracy or completeness. Furthermore, as a good friend/mentor of mine once reminded me when I was an undergrad, science requires error bars! These data have none that I could find.

The Std Dev may or may not be terribly useful, but I felt the means were quite illuminating. Here is the figure:

Figure 1: Top) Mean temperature reported vs GDP. Bottom) Mean water pH level reported, with standard deviations for each country shown as error bars. A linear least squares fit is provided in red.
As you can see from this figure there is a weak trend with GDP. Also curious to me was the apparent anti-correlation between temperature and GDP. Evidently, if you want to live in a well-to-do country, live somewhere cooler!

That furthest-right data point: the good 'ol USA of course! Several other name-brand western countries comprise the right-most portion of this figure (such as the UK, Canada, Australia). Noticeably absent from this data set: freshwater measurements from China.

Conclusion: There seems to be a weak trend, with water pH levels for more "developing" countries preferentially basic. Intermediate economies seem to be quite spread in pH levels. The most powerful nations continue the rough trend seen over four orders of magnitude in GDP: a decline from alkaline towards pure water.

The rough trend may seem encouraging for politicians, but the significant scatter represents both the intrinsic noise in the data, and a wider ecological issue. Consider that the USA has the highest economy listed by a wide margin, as well as one of the widest standard deviations in pH. Several countries with GDP's smaller than most American states have markedly better water quality. This supports the indication (mentioned in the abstract linked near the beginning) that it is not the GDP which contributes most to water quality. I am left thinking of a few better candidates: social/political forces, environmental regulations, natural resources, or maybe just number of trees...

That's enough wild (data-less) speculation for tonight I'd say.