After very nearly seven years online, and over 650,000 posts by its members, the time has come to shut the doors on the original Galaxy Zoo Forum. Originally an afterthought, created to deal with the fact that we couldn’t possibly deal with the volume of mail that we were getting, the Forum quickly established itself as a very special place. It generated science – the Voorwerp and its diminutive colleagues, the Voorwerpjes, the Peas and much more came from discussions amongst its boards, as well as such random fun things as the letters that power My Galaxies.
It was also a very civilized place – entirely due to the standards set by Alice and the team of moderators that followed, especially Graham and Hanny who have served most recently. The forum inspired much of what the Zooniverse tries to do today, but time has moved on and we have taken, in collaboration with the moderation team, the decision to shut the forum down. The vast majority of Galaxy Zoo volunteers now interact with each other via Talk, not the forum, and that’s where we want to concentrate our efforts. Closing the forum will allow us to abandon the archaic software that runs the forum itself, and free the moderators from the increasingly onerous task of clearing the forum of spam. It will be preserved intact as a valuable resource, and a record of discussion during the first seven years of Galaxy Zoo’s life.
Feedback and discussion about everything in the Zooniverse is still welcome, of course. As well as Talk, there are blog comments, and thanks to a recent grant from the Alfred P. Sloan Foundation, we’re going to be rebuilding Talk over the next few months. If you’d like to help shape the future of discussion and community in the Zooniverse, then there’s a form for feedback available here. I’m looking forward to reading what you have to say.
It’s always exciting to see a new Galaxy Zoo paper out, but today’s release of our latest is really exciting. Galaxy Zoo 2: detailed morphological classifications for 304,122 galaxies from the Sloan Digital Sky Survey, now accepted for publication in the Monthly Notices of the Royal Astronomical Society, is the result of a lot of hard work by Kyle Willett and friends.
Galaxy Zoo 2 was the first of our projects to go beyond simply splitting galaxies into ellipticals and spirals, and so these results provide data on bars, on the number of spiral arms and on much more besides. The more complicated project made things more complicated for us in turning raw clicks on the website into scientific calculations – we had to take into account the way the different classifications depended on each other, and still had to worry about the inevitable effect that more distant, fainter or smaller galaxies will be less likely to show features.
We’ve got plenty of science out of the Zoo 2 data set while we were resolving these problems, but the good news is that all of that work is now done, and in addition to the paper we’re making the data available for anyone to use. You can find it alongside data from Zoo 1 at data.galaxyzoo.org. One of the most rewarding things about the project so far has been watching other astronomers make use of the original data set – and now they have much more information about each galaxy to go on.
As announced on the Zooniverse blog, Oxford University Press have agreed that to make the Zooniverse papers published in Monthly Notices of the Royal Astronomical Society open access. While they’ve always been freely available on astro-ph, it’s nice that everyone who contributed can now get access – for free – via the main journal site.
This post, from Berkley statistician Joey Richards, is one of three marking the end of this phase of the Galaxy Zoo : Supernova project. You can hear from project lead Mark Sullivan here, and from the Zooniverse’s Chris Lintott here.
Thanks to the efforts of the Galaxy Zoo Supernovae community, researchers in the Palomar Transient Factory collaboration have constructed a machine-learned (ML) classifier that can reliably predict, in near real-time, whether each candidate is a real supernova. ML classification operates by employing previously vetted data to teach computer algorithms a statistical model that can accurately and automatically predict the class for each new candidate (i.e., real transient or not) from observed data on that object. The manual vetting of tens of thousands of supernova candidates by the Galaxy Zoo community has provided PTF an invaluable data set which could be used to accurately train such a ML classifier.
The ML approach is appealing for supernova vetting because it allows us to make probabilistic classification statements, in real-time, about the validity of each new candidate. Further, it allows the simultaneous use of many data sources, including both new and reference PTF imaging data, historical PTF light curves, and information from external, on-line sources such as the Sloan Digital Sky Survey and the U.S. Naval Observatory. In total, our automated ML algorithms use 58 metrics about each supernova candidate, all of which are available within seconds after PTF detection of the candidate. These metrics—features in ML parlance—are fed into a sophisticated algorithm, which uses the aggregate of information from more than 25,000 historical supernova candidates which were rated by the Zoo to instantaneously determine whether each newly observed candidate is a supernova.
Our “ML Zoo” has been operating since the beginning of 2012 and has been thoroughly tested against the Human Zoo scores. We found that the ML Zoo scores correlate reasonably well with the average Human Zoo scores for 7000 supernova candidates observed during the first 3 months of 2012 (Figure 1). We also discovered that the ML Zoo is more effective at finding supernovae. In Figure 2 we show a plot of the supernova false positive rate (% of non-supernovae that were classified as supernovae) versus the supernova missed detection rate (% of confirmed supernovae that were classified as a non-supernovae) by both the Human an ML Zoos for 345 spectroscopically confirmed supernovae from 2010. Indeed, the ML Zoo achieves a smaller missed detection rate at each false positive rate.
Joseph Richards works in the Statistics and Astronomy departments at
the University of California, Berkeley as an NSF-sponsored
postdoctoral researcher supported by an interdisciplinary
Cyber-enabled Discovery and Innovation grant. His main area of focus
is astrostatistics and he holds a Ph.D. in Statistics from Carnegie
Mellon University. In his academic research, he has developed
sophisticated statistical and machine learning methodologies to
analyze large collections of astronomical data.
This post, from project lead Mark Sullivan of Oxford, is one of three marking the end of this phase of the Galaxy Zoo : Supernova project. You can hear from Joey Richards of PTF here, and from the Zooniverse team here.
Since August 2009, Galaxy Zoo Supernovae has been helping astronomers in the Palomar Transient Factory (PTF) find exploding stars, or supernovae, in imaging data taken with a telescope in Southern California. This project has been tremendously successful – Galaxy Zoo Supernovae has uncovered hundreds of supernovae in the PTF data that would otherwise have been missed. These discoveries have directly resulted in scientific publications, with many more in the pipeline, and have been observed on telescopes all over the world, including the 4.2-metre William Herschel Telescope. For example, my colleague Dr. Kate Maguire’s paper includes 8 supernovae found by the Zoo, which were subsequently observed using the Hubble Space Telescope. This allowed her to examine the ultraviolet properties of several thermonuclear ‘type Ia’ supernovae, the same type as those used in the original discovery of dark energy and the accelerating universe. The ultraviolet is a probe of the composition of the exploding star, and allowed her to test whether type Ia supernova properties change with time as the universe ages and becomes enriched with heavy elements.
But – all good things must come to an end. One of the goals of Galaxy Zoo Supernovae was to use the Zoo classifications to improve the algorithms that surveys such as PTF use to find supernovae automatically. And the good news is that, after two years of hard work, we have managed to do just that. The full details are explained in a separate blog posting by Dr. Joey Richards at the University of California at Berkeley.
I’d like to take this opportunity, on behalf of everyone involved with PTF, to thank you all for your time and effort in classifying these supernovae for us. We realise how much effort you’ve put in, and it has been very much appreciated.
For those of you who have become addicted to supernovae, don’t panic – there may be further supernova-related projects in a few months time. In the mean-time, watch this space for more publications based on Galaxy Zoo Supernovae discoveries!
I used to think that science was about discovery, about adding certainty to what we know about the Universe. Discoveries happen, of course, but I’ve learned that the really exciting stuff happens not when we expand our knowledge, but our ignorance; progress is measured in the number of unanswered questions we have. After all, any good result raises more of those than it answers.
I have this in mind because today is the 5th anniversary of the launch of Galaxy Zoo, and it’s tempting to write about how we – with your help – have magnificently fulfilled the vision we had back in 2007. After all, in that first story on the BBC news website; a youthful version of me chirps that “We hope that participants in Galaxy Zoo will not only contribute to science, but have a lot of fun along the way”. Science? Check. Fun? Check..
But did we really understand what we were getting into? Certainly not. We’ve rehearsed before the story that we didn’t understand the size of the response we would get, nor the undimmed enthusiasm for sharing in exploring the Universe that still motivates volunteers today. But on launch, we didn’t realize we needed this blog to explain what we were doing with the clicks, nor the forum; which (thanks to the efforts of Alice Sheppard and team) has played such an important role in defining Galaxy Zoo. We didn’t realize that detailed classifications, of bars and three-armed spirals, of bulgeless disks and merging galaxies, were possible, nor that thanks to the Hubble Space Telescope we’d end up exploring the distant Universe, peering at blue blobby galaxies in a mixture of interest, awe and frustration.
We didn’t realize that spontaneous discovery, serendipitous exploration of the cosmos would come to provide some of the most entertaining and scientifically valuable results from the project. From the Voorwerp, to the recent Hubble images of the Voorwerpjes; (another hit my inbox this morning – watch this space) through to the Peas which are now attracting rather a lot of attention). On a personal note, on that July morning in 2007 I didn’t know most of the people who would lead this scientific return – Kevin, of course, was still recovering from classifying 50,000 galaxies himself, and Kate Land and Anze Slosar provided sterling support, but Steven Bamford and Karen Masters in particular had yet to step forward into their leading roles. Much of this science will be celebrated at a one day meeting at the Royal Astronomical Society next year on ‘Galaxy Morphology in the era of large surveys’ – mark your diaries for May 10th! The most exciting work to be presented at that meeting probably doesn’t exist yet – I suspect we’ll still be puzzling over exactly what bars do to galaxies (or vice versa), and arguing about exactly how black holes grow, but all we have at the moment is an ever-growing pile of questions. Which is, of course, exactly as it should be.
We also didn’t know what we didn’t know when it came to development. The original site worked brilliantly, thanks to the efforts of Phil Murray; and Dan Andreescu, but probably the biggest change over the last few years has been the arrival of Arfon Smith and his merry band of developers. That, of course, has spawned a whole new Zooniverse, which has sent us hunting for supernovae, planets, looking for bubbles and even listening to whales. In that manic expansion, Galaxy Zoo has occasionally been left behind, but I’m pleased to say that a new site is on the way. By the middle of August, a brand new site will be serving up images of new galaxies, both from the deep CANDELS survey and, returning to our roots, from the latest data release of the Sloan Digital Sky Survey. We do need to have a few more clicks on the existing site, though, so anyone who classifies in the next two weeks on Galaxy Zoo will be rewarded with early access to the new site (whether or not you’re still reading at this point).
So much for the next few weeks. What of the next few years? I could tell you that as Galaxy Zoo has established citizen science as a standard way of doing astronomy, you’ll see many more projects from us exploring pretty much every aspect of the Universe. I could tell you that I suspect that live interaction with data fresh from the telescope; is going to be increasingly important as the amount of data available to astronomers reaches at least 120 terabytes by the end of the decade. I could spend hundreds or thousands of words convincing you that advanced tools are key, that we’re going to need many more people to follow the lead of the denziens of the forum and get deeply involved in the science that lies beyond clicking. And I could tell you of our determination to finally crack a means of getting Galaxy Zoo firmly into the classroom, but the truth is anything could happen. And that’s just the way we like it.
P.S. To anyone who has taken part in the last 5 years – thanks a million. Now go and get classifying.