This isn't your grandfather's stargazing: The amount of data we have on our universe is doubling every year thanks to big telescopes and better light detectors.
Think of all the data humans have collected over the long history of astronomy, from the cuneiform tablets of ancient Babylon to images---like the one above---taken by the Hubble Space Telescope. If we could express all of that data as a number of bits, our fundamental unit of information, that number would be, well, astronomical. But that's not all: in the next year that number is going to double, and the year after that it will double again, and so on and so on.
There are two reasons that astronomy is experiencing this accelerating explosion of data. First, we are getting very good at building telescopes that can image enormous portions of the sky. Second, the sensitivity of our detectors is subject to the exponential force of Moore's Law. That means that these enormous images are increasingly dense with pixels, and they're growing fast---the Large Synoptic Survey Telescope, scheduled to become operational in 2015, has a three-billion-pixel digital camera. So far, our data storage capabilities have kept pace with the massive output of these electronic stargazers. The real struggle has been figuring out how to search and synthesize that output.
Alberto Conti is the Innovation Scientist for the James Webb Space Telescope, the successor to the Hubble Space Telescope that is due to launch in 2018. Before transitioning to the Webb, Conti was the Archive Scientist at the Space Telescope Science Institute (STScI), the organization that operates the Hubble. For almost ten years, he has been trying to make telescope data accessible to astronomers and to the public at large. What follows is my conversation with Conti about the future of, and the relationship between, big telescopes and big data.
Last year I was researching the Hubble Deep Field (pictured below) and I interviewed
Bob Williams, the former head of STScI who originally conceived of and
executed the deep field image. He told me that the deep field, in
addition to its extraordinary scientific value, had changed the way that
data is distributed in astronomy. Can you explain how?
It's interesting, one of the very first papers I wrote as a graduate
student in astronomy was on the Hubble Deep Field. I was a graduate
student in 1995 when it came out, and of course there was this "wow"
factor---the fact that this was one of the deepest images ever taken,
the fact that you have thousands of galaxies in this tiny patch of
sky---you would take out your calculator and try to calculate how many
galaxies there are in the universe and you would come up with a hundred
billion, and it was mind-boggling. It still is.
it also changed the data regime. Before the Hubble Deep Field, data
(raw images) would be deposited in some archive and you would just tell
astronomers to "go get the images." Astronomers would then have to
download the images and run software on them in order to find all of the
objects using certain parameters, and then they'd have to assess the
quality of the data, for instance whether an object that was thought to
be a star was actually a star. So you had to do a lot of analysis before
you could really get into your research.
decided that this data was so overwhelmingly powerful, in terms of what
it was telling us about the universe, that it was worth it for the
community to be able to get their hands on the data immediately. And so
the original deep field team processed the data, found the objects in
it, and then catalogued each of them, so that every object in the deep
field had a description in terms of size, distance, color, brightness
and so forth. And that catalogue was available to researchers from the
very start---it started a whole new model, where the archive does all
I can tell you firsthand how
incredible it was at the time, because as a graduate student studying
quasars, I was able to identify all of the quasars within the data in
just a few minutes. What Bob did, which I thought was brilliant, was
enable us to do the science much quicker. If you take a look at what's
happening with these massive archives now, it's being done in the exact
same way; people realized that you aren't going to be able to download
and process a terabyte of images yourself. It's a huge waste of time.
The other thing Bob did was he released the data to the world almost
immediately; I remember it took forever to download, not because the
data set was especially large, but because there were so many people
accessing the archive at the same time. That was one of astronomy's
first open source exercises, in the sense that we use that term today.
Has data always been an issue for astronomy? Did Galileo ever run out of log books? I remember reading about William Herschel's sister Caroline, an accomplished astronomer in her own right, spending these long, cold nights underneath their wooden telescope, listening for her brother, who would scream these numbers for her to write down in a notebook. How have data challenges changed since then?
Conti: That's a good question. Astronomy has changed quite a bit since Galileo and Herschel. Galileo, for instance, had plenty of paper on which to record his observations, but he was limited in his capacity for observation and so was Herschel to some extent. Today we don't have those same observational limits.
There are two issues driving the current data challenges facing astronomy. First, we are in a vastly different data regime in astronomy than we were even ten or fifteen years ago. Over the past 25 to 30 years, we have been able to build telescopes that are 30 times larger than what we used to be able to build, and at the same time our detectors are 3,000 times more powerful in terms of pixels. The explosion in sensitivity you see in these detectors is a product of Moore's Law---they can collect up to a hundred times more data than was possible even just a few years ago. This exponential increase means that the collective data of astronomy doubles every year or so, and that can be very tough to capture and analyze.
You spent part of your career working with GALEX, the Galaxy Evolution Explorer. How did that experience change the way you saw data and astronomy?
Conti: GALEX was a big deal because it was one of the first whole sky ultraviolet missions. I want to stress "whole sky" here, because taking measurements of ultraviolet sources all over the sky is a lot more data-intensive than zooming in on a single source. Whole sky ultraviolet measurements had been done before, but never at the depth and resolution made possible by GALEX. This had tremendous implications for data archives at the time. When I started working on GALEX nine years ago, the amount of data it produced was gigantic compared with anything that we had in-house at the Space Telescope Science Institute, and that includes the Hubble Space Telescope, which of course doesn't take whole sky images.
What we were able to do was create a catalog of objects that were detected in these whole sky images, and the number was quite large---GALEX had detected something close to three hundred million ultraviolet sources in the sky. That forced the archive to completely revisit the way it allowed users to access these very large catalogs. There were large databases in astronomy ten years ago, but databases that would allow you to search large collections of objects were not common. GALEX helped to pave the way with this new searchable archive. I can remember when we first introduced the data, we had people all over the world trying to download all of the data, because they thought that was the only way they could access it. They were thinking that to use the data you had to have it locally, which was the old way of thinking. The big leap was that we created an interface that allowed you to get to your data, to a level where you're one step away from analysis, and we were able to do that without you having to download it. We did it by creating interfaces that allowed you to mine all three hundred million sources of ultraviolet light in just a few seconds. You could ask the interface to show you all of the objects that had a particular color, or all of the sources from a certain position in the sky, and then you could download only what you needed. That was a big shift in how astronomers do research.
How much data are we talking about?
Conti: Well, GALEX as a whole produced 20 terabytes of data, and that's actually not that large today---in fact it's tiny compared to the instruments that are coming, which are going to make these interfaces even more important. We have telescopes coming that are going to produce petabytes (a thousand terabytes) of data. Already, it's difficult to download a terabyte; a petabyte would be, not impossible, but certainly an enormous waste of bandwidth and time. It's like me telling you to download part of the Internet and search it yourself, instead of just using Google.
Would something like the exoplanet-hunting Kepler Space Telescope have been possible with the data mining and data storage capacities of twenty years ago?
Conti: Well, Kepler is an extraordinary mission for many reasons. Technologically, it would not have been possible even just a few years ago. Kepler measures the light of 170,000 stars very precisely at regular intervals looking for these dips in light that indicate a planet is present. The area that they sample is not very large---it's a small patch of sky---but they're sampling all of those stars every thirty minutes. So that's already a huge breakthrough, and it creates a lot of data, but it's still not as much as a whole sky mission like GALEX.
What's different about Kepler, from a data perspective, is that it's opening up the time domain. With a mission like GALEX, we collect data and store it in the database, but it's relatively static. It sits there and it doesn't really change, unless we get a new dump of data that helps us refine it, and that may only happen once a year. With Kepler you have these very short intervals for data collection, where you have new images every thirty minutes. That really opens up the time domain. We're working hard to figure out how to efficiently analyze time domain data. And of course the results are spectacular: a few years ago we had less than twenty exoplanets, and now we have thousands.
Is there a new generation of telescopes coming that will make use of these time domain techniques?
Conti: Oh yes. With Kepler we've developed this ability to make close observations of objects in the sky over time, but if you add millions or even billions of objects, then you get into the new regime of telescopes like the Large Synoptic Survey Telescope (LSST) which we expect to come online at the end of this decade. These telescopes are going to take images of the whole sky every three days or so; with that kind of data you can actually make movies of the whole sky. You can point to a place in the sky and say "there was nothing there the other day, but today there's a supernova." You couple that kind of big data, whole sky data, with the time domain and you're talking about collecting terabytes every night. And we don't have to wait that long; ALMA, the Atacama Large Millimeter Array is going to have its first data release very soon and its raw data is something like forty terabytes a day. Then in 2025, we're going to have the Square Kilometre Array (SKA), the most sensitive radio instrument ever built, and we expect it will produce more data than we have on the entire Internet now---and that's in a single year. This is all being driven by the effect that Moore's Law has on these detectors; these systematic advances let us keep packing in more and more pixels.
In my view, we've reached the point where storage is no longer the issue. You can buy disk, you can buy storage, and I think that at some point we may even have a cloud for astronomy that can host a lot of this data. The problem is how long it's going to take me to get a search answer out of these massive data sets. How long will I have to wait for it?
Has citizen science played a meaningful role in helping astronomy tackle all of this data?
Conti: I think so. I'm part of a group that has done a lot of work on citizen science, especially with the folks over at Galaxy Zoo and CosmoQuest on an in-house project called Hubble Zoo. The original Galaxy Zoo was a galaxy classification project, where volunteers could log on to the server and help to classify galaxies by shape. Galaxy shapes give you a lot of information about their formation history; for instance, round galaxies are much more likely to have cannibalized other galaxies in a merger, and on average they're a little older. Spiral galaxies are structures that need time to evolve; generally, they're a little younger than round galaxies. And so when you have thousands of ordinary, non-scientists classifying these galaxies you can get some great statistics in a short period of time. You can get the percentage of round galaxies, elliptical galaxies, spiral galaxies, irregular galaxies and so forth; you can get some really interesting information back. What's great about citizen science is that you can feed images to citizens that have only been fed through machines---no human eyes have ever looked at them.
There's another citizen science project that I'm trying to get started in order to to make use of all the old GALEX data. With GALEX we took these whole sky images in ultraviolet, and we did it at certain intervals, so there is a time domain at work, even if it's not as rapid as the Kepler. But as I said before, we have over three hundred million sources of UV light in these images. There was a professor who had a graduate student looking at this data at different intervals with the naked eye, and they were able to find four hundred stars that seemed to be pulsating over time. When I saw the data, I said "this is interesting, but it should be an algorithm." So we made an algorithm to detect these pulsating stars, and we ran it inside the entire database of 300 million sources, and we found 2.1 million pulsating star candidates. And of course, this is just the first pass at this; who knows how many of those candidates will convert. But it's an illustrative case---the idea is to feed these kinds of projects to the next generation of citizen scientists, and to have them to do what that graduate student did, and then in some cases they'll be able to find something remarkable, something that otherwise might never have been found.
Can we talk about image-processing? What percentage of Hubble images
are given the kind of treatment that you see with really iconic shots
like the Sombrero Galaxy or the Pillars of Creation?
It depends. There's an image coming out for the 22nd anniversary (of
the Hubble) here in a few days, and as you'll be able to see, it's a
very beautiful image. I'm a little biased in the sense that I tend to
think that every image from the Hubble is iconic, but they aren't all
treated equally. There's a group of people here in the office of public
outreach at STScI that think a lot about how images are released. But if
you go back to the Hubble Deep Field, or even earlier, you can see that
the imaging team really does put a lot of care into every Hubble image.
And that's not because each one of those images is iconic; rather it's
because we have this instrument that is so unbelievable and each piece
of data it produces is precious, and so a lot of work goes into
And now, with the Hubble
Legacy Archive, people can produce their own Hubble images, with new
colors, and they can do it on the fly.
Like Instagram filters?
Kind of, yeah. As you know, all data in astronomy is monochrome
data---it's black and white---and then the processing team combines it
into layers of red, green and blue, and so forth. Zolt Levay, the head
of the imaging team, takes these colored layers and combines them and
tries to make them as accurate as possible in terms of how they would
look to the human eye, or to a slightly more sensitive eye. This program
lets you take three monochrome images, which you can then make any
color you like, and it let's you make them into a single beautiful
image. There's actually a contest being held by the office of public outreach to see who can upload the most beautiful new image.
Forget the Common Core, Finland’s youngsters are in charge of determining what happens in the classroom.
“The changes to kindergarten make me sick,” a veteran teacher in Arkansas recently admitted to me. “Think about what you did in first grade—that’s what my 5-year-old babies are expected to do.”
The difference between first grade and kindergarten may not seem like much, but what I remember about my first-grade experience in the mid-90s doesn’t match the kindergarten she described in her email: three and a half hours of daily literacy instruction, an hour and a half of daily math instruction, 20 minutes of daily “physical activity time” (officially banned from being called “recess”) and two 56-question standardized tests in literacy and math—on the fourth week of school.
That American friend—who teaches 20 students without an aide—has fought to integrate 30 minutes of “station time” into the literacy block, which includes “blocks, science, magnetic letters, play dough with letter stamps to practice words, books, and storytelling.” But the most controversial area of her classroom isn’t the blocks nor the stamps: Rather, it’s the “house station with dolls and toy food”—items her district tried to remove last year. The implication was clear: There’s no time for play in kindergarten anymore.
Even in big cities like Tokyo, small children take the subway and run errands by themselves. The reason has a lot to do with group dynamics.
It’s a common sight on Japanese mass transit: Children troop through train cars, singly or in small groups, looking for seats.
They wear knee socks, polished patent-leather shoes, and plaid jumpers, with wide-brimmed hats fastened under the chin and train passes pinned to their backpacks. The kids are as young as 6 or 7, on their way to and from school, and there is nary a guardian in sight.
A popular television show called Hajimete no Otsukai, or My First Errand, features children as young as two or three being sent out to do a task for their family. As they tentatively make their way to the greengrocer or bakery, their progress is secretly filmed by a camera crew. The show has been running for more than 25 years.
Some businesspeople are working half of the week in far-off countries or catching 3 a.m. trains just so that they don’t have to uproot their lives at home.
A few years back, David Neeleman, the founder of JetBlue Airways, left his company and launched a new airline in Brazil. The airline, Azul, flies 22 million people a year, employs 12,000 people, and is the fastest-growing carrier in the region.
You’d think running such a large, complex operation would require a move to South America. But Neeleman commutes to Azul’s Sao Paulo headquarters every week from his home in Connecticut, taking the 10-hour redeye on Sunday nights and returning on Thursdays. This way, he says, he doesn’t have to uproot his family of 10 kids.
“My wife wasn’t so interested in moving,” said Neeleman, who recently bought TAP, Portugal’s national airline and is now commuting there as well. “We had all these kids playing [American] football and lacrosse. They don’t have those sports in Brazil.”
In the movie Up in the Air, George Clooney successfully captures the road-warrior ethos that has long been associated with, say, business consultants from firms like McKinsey & Company who work on projects outside their hometowns and spend most of their week in hotels. But now, more and more executives around the world are choosing to take on lengthy commutes on a permanent basis, even if their jobs don’t demand it. Increasing globalization and tech-enabled workplace flexibility are certainly part of the reason why. But a more child-centered approach to parenting also seems to be a factor, as these executives make other major sacrifices in order to balance their professional and home lives.
A new study finds that people today who eat and exercise the same amount as people 20 years ago are still fatter.
There’s a meme aimed at Millennial catharsis called “Old Economy Steve.” It’s a series of pictures of a late-70s teenager, who presumably is now a middle-aged man, that mocks some of the messages Millennials say they hear from older generations—and shows why they’re deeply janky. Old Economy Steve graduates and gets a job right away. Old Economy Steve “worked his way through college” because tuition was $400. And so forth.
We can now add another one to that list: Old Economy Steve ate at McDonald’s almost every day, and he still somehow had a 32-inch waist.
A study published recently in the journal Obesity Research & Clinical Practice found that it’s harder for adults today to maintain the same weight as those 20 to 30 years ago did, even at the same levels of food intake and exercise.
Your income, how long you dated, and how many people attend your wedding affect the odds you'll stay together.
A diamond is forever, but an expensive engagement ring means the marriage might not last that long. According to a new study, spending between $2,000 and $4,000 on an engagement ring is significantly associated with an increase in the risk of divorce.
The data scientist Randal Olson recently visualized some of the findings from a paper by Andrew Francis and Hugo Mialon, two researchers at Emory University who studied 3,000 married couples in the U.S. to determine the factors that predicted divorce. They analyzed income, religious attendance, how important attractiveness was to each partner, wedding attendance, and other metrics to determine the aspects associated with eventual marital dissolution.
Any attempt to address mass incarceration has to begin with an effort to tackle crime—and the social conditions linked to its rise.
With the publication of “The Black Family in the Age of Mass Incarceration” Ta-Nehisi Coates has added an elegant and forceful voice to the growing frustration with the inefficacy and injustice of America’s criminal-justice system. Mandatory-sentencing laws, the War on Drugs, juvenile-justice sentences that seem to do more to create than deter criminals, racial arrest and sentencing disparities: All are ready for a tough national cross-examination.
But even in the unlikely event that Washington and state legislatures successfully adapt the nation’s crime policies to a safer, more racially sensitive era, the nation will still look around to find more black men in prison than it might expect or want. There’s a simple reason for that, one that Coates himself notes: Relative to other groups, blacks commit more crimes. To understand why is to tackle some very hard-to-talk-about realities of black family life. And on that issue—and despite his announced interest in the topic—Coates has been the opposite of lucid.
In the name of emotional well-being, college students are increasingly demanding protection from words and ideas they don’t like. Here’s why that’s disastrous for education—and mental health.
Something strange is happening at America’s colleges and universities. A movement is arising, undirected and driven largely by students, to scrub campuses clean of words, ideas, and subjects that might cause discomfort or give offense. Last December, Jeannie Suk wrote in an online article for The New Yorker about law students asking her fellow professors at Harvard not to teach rape law—or, in one case, even use the word violate (as in “that violates the law”) lest it cause students distress. In February, Laura Kipnis, a professor at Northwestern University, wrote an essay in The Chronicle of Higher Education describing a new campus politics of sexual paranoia—and was then subjected to a long investigation after students who were offended by the article and by a tweet she’d sent filed Title IX complaints against her. In June, a professor protecting himself with a pseudonym wrote an essay for Vox describing how gingerly he now has to teach. “I’m a Liberal Professor, and My Liberal Students Terrify Me,” the headline said. A number of popular comedians, including Chris Rock, have stopped performing on college campuses (see Caitlin Flanagan’s article in this month’s issue). Jerry Seinfeld and Bill Maher have publicly condemned the oversensitivity of college students, saying too many of them can’t take a joke.
David Hume, the Buddha, and a search for the Eastern roots of the Western Enlightenment
In2006, i was 50—and I was falling apart.
Until then, I had always known exactly who I was: an exceptionally fortunate and happy woman, full of irrational exuberance and everyday joy.
I knew who I was professionally. When I was 16, I’d discovered cognitive science and analytic philosophy, and knew at once that I wanted the tough-minded, rigorous, intellectual life they could offer me. I’d gotten my doctorate at 25 and had gone on to become a professor of psychology and philosophy at UC Berkeley.
I knew who I was personally, too. For one thing, I liked men. I was never pretty, but the heterosexual dance of attraction and flirtation had always been an important part of my life, a background thrum that brightened and sharpened all the rest. My closest friends and colleagues had all been men.
Not all purveyors of art think the male form gets enough attention. Exhibitions like Sascha Schneider’s show at the Leslie Lohman Museum of Gay and Lesbian Art have highlighted the importance of the male nude and its relationship to history; but others, including the recent "Masculine/Masculine" retrospective at the Musée d'Orsay, have prompted the question: "Why had there never been an exhibition dedicated the male nude until … last year?" The answer: Unlike female bodies, which are supposedly mysterious and full of secrets, male bodies are boring—or at least they're presented that way. A new book, Universal Hunks: A Pictoral History of Muscular Men Around the World, 1895-1975, provides a little more perspective.
American politicians are now eager to disown a failed criminal-justice system that’s left the U.S. with the largest incarcerated population in the world. But they've failed to reckon with history. Fifty years after Daniel Patrick Moynihan’s report “The Negro Family” tragically helped create this system, it's time to reclaim his original intent.
By his own lights, Daniel Patrick Moynihan, ambassador, senator, sociologist, and itinerant American intellectual, was the product of a broken home and a pathological family. He was born in 1927 in Tulsa, Oklahoma, but raised mostly in New York City. When Moynihan was 10 years old, his father, John, left the family, plunging it into poverty. Moynihan’s mother, Margaret, remarried, had another child, divorced, moved to Indiana to stay with relatives, then returned to New York, where she worked as a nurse. Moynihan’s childhood—a tangle of poverty, remarriage, relocation, and single motherhood—contrasted starkly with the idyllic American family life he would later extol.