Go on virtual safari with our latest project: Snapshot Serengeti! Serengeti National Park is a UNESCO World Heritage Site in Tanzania. With an area of nearly 6,000 square miles (14,800 km^2) it is teeming with some of the most recognisable animals in the world: lions, zebra, elephants, wildebeest and more live on the vast savannah and grassland plains.

Researchers at the University of Minnesota have been trying to count and locate the animals of the Serengeti, and began placing automatic cameras across the park a couple of years ago. They now have more than 200 cameras around the region – all triggered by motion – capturing animals day and night. They have amassed millions of images so far, and more come in all the time. So they’ve team up with us here at the Zooniverse! They need the help of online volunteers to spot and classify animals in these snapshot of  life in Serengeti National Park. Doing this will provide the data needed to track and study these animals, whilst giving everyone the chance to see them in the wild.

Snapshot Serengeti also launches a new version of our discussion tool, Talk. You can chat about the images you see, as well as collect them together and ask questions of the researchers and the community at large. Learn more about the project, and the team behind it, on the Snapshot Serengeti Blog or check out the site right now at http://www.snapshotserengeti.org

[Follow @snapserengeti on Twitter and check out the Facebook page too.]

We’ve teamed up with astronomers in the US who need your help to search Hubble Space Telescope images of the Andromeda galaxy. This brand new citizen science project is called The Andromeda Project and can be found at http://www.andromedaproject.org. We need volunteers to help identify star clusters and help increase understanding of how galaxies evolve.

There may be as many as 2,500 star clusters hiding in Hubble’s Andromeda images, but only 600 have been identified so far in months of searching, and star clusters tend to elude pattern-recognition software. The seo company researchers decided it’s something that everyone can help with, even without extensive training. Volunteers will vote, by marking clusters, on the identity and location of star clusters.

Star clusters are dense groups of stars that are born together from the same cloud of gas. Their common age make them useful for studying the evolution of galaxies and the properties of stars. Andromeda, also called Messier 31 or M31, is the closest spiral galaxy to our own Milky Way, which is similar. Though a neighbor in the galactic sense, Andromeda is 2.4 million light years from the Earth. That translates into about 14 billion billion miles.

There are more than 10,000 images waiting at http://www.andromedaproject.org – they all come from the Panchromatic Hubble Andromeda Treasury, or PHAT for short. The goal of the PHAT survey is to map about one-third of Andromeda’s star-forming disk, through six filters spread across the electromagnetic spectrum — two ultraviolet, two visible and two infrared.

The Hubble telescope started gathering images for the treasury in 2010 and is expected to send its last batch of images back to Earth in the summer of 2013. The Andromeda Project aims to produce the largest catalog of star clusters known in any spiral galaxy.

You can also find our new project on Twitter @andromedaproj and on Facebook too.

September 2012 is going to be a month like no other in the history of the Zooniverse! We have lots of new projects lined up – including some that are really different from anything we’ve tried before. We’re so excited that we’ve even given the month a name – Citizen Science September – and a logo, and we’ll use these to help bring you up to speed with the new projects as well as encouraging you to re-explore some existing ones.

It all began back in 2007 when Galaxy Zoo asked for the public’s help in classifying a huge database of galaxies. The response was overwhelming and since then we’ve launched more than 10 citizen science projects. Some of those projects have come to a conclusion, having helped researchers and provided valuable data. Some have evolved and changed, and others keep rolling as the data keeps coming in. We’ve have asked for your help in mapping the galaxy, finding exoplanets, transcribing ancient texts, listening to whale calls, distinguishing wild garcinia cambogia plants from green coffee leaves and even sailing the high seas – just to name few ways that our volunteers have been aiding scientists in their work.

What began with astronomy has spread out to include climate science, marine biology and papyrology. During September (and beyond) you’ll see even more areas of research brought into the Zooniverse fold. We’re really excited to introduce these exciting new projects to you and to introduce new communities to the Zooniverse. There will also be major updates to some of our existing projects.

To follow progress during Citizen Science September follow us on Twitter or on Facebook we’ll be bring you updates from across our projects and introducing new ones.

This is just a quick note to let you know that we’ve updated the Zooniverse privacy policy, and that you can see the new version here. In truth, I don’t think there’s anything that surprising in there, but as we continue to grow we thought it was good to be much more explicit about what data we collect, and what we do with it.

We’re also now required to explicitly tell you that we’re using cookies for some features of the site, and you’ll see pop-ups that inform you of this fact appear in the next few days. Once selected, they should go away.

If you have any concerns, you can get in touch with the team by emailing support AT zooniverse.org.

This post, from Chris Lintott, 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 machine learning expert and statistician Joey Richards here.

Today’s a bittersweet day for us, as the Galaxy Zoo : Supernova project moves off into (perhaps temporary) retirement. You can read about the reasons for this change over on the Galaxy Zoo blog, but the short answer is that the team have used the thousands of classifications submitted by volunteers to train a machine that can now outperform the humans. Time to wheel out this graphic again, last posted when we started looking at teaching machines with Galaxy Zoo data.

That’s all very well, but what of those of us who enjoyed the thrill of hunting for supernovae? I think there are two reasons to believe that the supernova project or something very like it will be back someday soon. Firstly, the machine learning solution is now very good at finding supernovae in images from just one search, the Palomar Transient Factory. I suspect other surveys, with their own quirks, may require a training set as large as that used for PTF. I suspect we’ll see a pattern developing in which the early months or years of a survey require volunteer classification, before relaxing until the next challenge comes along. We’re hoping to test this idea sometime soon.

The second way in which I think human classification will return is more subtle – we need to make friends, and collaborate with, the robots themselves. At the minute, for mostly practical reasons, we see this as a choice between the two, but the Zooniverse team and more than a few friends have started building a more sophisticated system which combines the two approaches.

One piece of that system is already in place, and owes a lot to the supernova project. Edwin Simpson and colleagues from Oxford’s Robotics SEO Consultant Research Group and the Zooniverse have built a mathematical model that’s capable of combining results from many different classifiers, measuring their performance and deciding who to listen to, and when. It was developed and tested using the supernova project data and has also been running live and keeping track of what’s happening. This should lead to an improvement in classification accuracy, but there’s more. The same sort of method could be used to combine human and machine classification, and we’re beginning to work on a system that can make decisions about when it’s worth asking humans for help. That allows us the best of both worlds – we’ll get to take advantage of machines for routine tasks, but allow them to call for our help when they get stuck. The result should be a more interesting project to participate in, a greater scientific return and the certainty that we’re not wasting your time. That all sounds pretty good to me.

During our last advent calendar we celebrated that our community had reached a total of 350,000 people. It’s been an incredible year. Several new projects, lots of fun and many scientific papers later – we expect to reach half a million Zooniverse users in the next day or so. Regardless of exactly when it happens, we want to say thank you to all of you ‘zooites’ out there for continuing to make our projects a big success.

Your feedback, dedication and clicks have really been paying off this year. We’ve seen multiple projects publish their first science results and there are many more on the way in 2012. Next year we expect to launch even more great projects that will allow citizen scientists to assist researchers in even more fields of work, across the world. Watch this space!

In the meantime – what exactly do 500,000 people look like? Wolfram Alpha reports that it’s the number of people who attended Woodstock in 1969. It also says that our community weigh roughly 35,000 metric tons, which is two-thirds the mass of the Titanic. The Zooniverse community generate 35 MW of power when considered as human batteries: that’s enough to supply 10,000 homes! Laid end-to-end 500,000 people stretch roughly 500 miles (~800 km) – which is of course how far the Proclaimers wold have walked.

500,000 people could fill Wembley Stadium 5 times over. Standing side-by-side they could fill the vatican, and there are only 9 armies in the world larger than the Zooniverse (China, USA, India, North Korea, Russia, South Korea, Pakistan, Iran and Turkey). We overtake turkey at 510,000 people – it won’t be long.

UPDATE:

We You did it – our 500,000th citizen scientist was ‘OHMfighter’! Here’s to the next half million! We also wanted to point everyone to their ‘My Project’ pages on the Zooniverse home page, where you can see your classification counts for all our projects. Visit http://zooniverse.org/projects/current to see your stats.

We’re beginning on a new project utiltizing Galaxy Zoo data.

Some background: Active Galactic Nuclei (AGN) are accreting supermassive black holes at the centers of some galaxies. In some of these systems, we observe broad and narrow emission lines in the optical spectra whereas other systems only have narrow emission lines. (In the spectra of normal galaxies that don’t have an active nucleus, we generally don’t see these prominent emission lines. In AGN, photons from the accretion disk photoionize the surrounding gas, causing the emission lines we observe.)

The unified model for AGN explains these observational differences by invoking an obscuring torus (or doughnut) of dust and gas that surrounds the accretion disk feeding the black hole. For a helpful visualization, look here. (Keep in mind that this picture is “zoomed-in” to the center of the galaxy.) If this configuration is aligned so that we’re looking through the opening of the torus, we can see the emission from the accretion disk and gas that’s moving rapidly due to its proximity to the black hole (which causes the broad emission lines in the optical spectra, and the gas from this region is subsequently referred to as the “Broad Line Region”). These sources are classified as Type 1 AGN. If, however, the system is aligned such that the torus is edge-on, that accretion disk and fast moving gas is blocked from our view. We will therefore see emission from gas that is further away from the black hole but close enough to be photionized by accretion disk photons, producing narrow emission lines (and no surprise, this region is called the “Narrow Line Region”). These AGN are Type 2 AGN, sometimes referred to as “obscured AGN” since the central region is hidden from our view.

The hypothesis: These AGN live in galaxies. Are our optical classifications of Type1/Type2 related to the orientation of the host galaxy? Do Type 1 (face-on) AGN preferentially live in face-on galaxies? Do Type 2 (edge-on) AGN tend to inhabit edge-on galaxies? The issue of the alignment of the torus with host galaxy inclination has been studied quite a bit in the past. In local AGN (called Seyfert galaxies), there is a lack of Type 1 systems in edge-on galaxies, but Type 2 AGN seem live in galaxies with any orientation (Keel 1980, Schmitt et al. 1997, Simco et al. 1997, Kinney et al. 2000).

The project: These past studies have been limited to relatively small sample sizes (under 100 galaxies). The Sloan Digital Sky Survey has spectra for hundreds of thousands of objects and Galaxy Zoo has classified thousands of galaxies. Combining these two rich data sets, we can test the above hypothesis with a sample size of several thousand galaxies.

I will blog updates as the project proceeds, so stay tuned to see where this journey takes us!

Today the Zooniverse launched Whale FM a new project in partnership with Scientific American. We have been working with marine biologists and have collected together more than 16,000 recordings of Whale calls. These calls come from Killer Whales and Pilot Whales – both actually species of dolphin! – and we need your help with listening to them. Whales can talk to each other in quite sophisticated ways. For example, each family of Killer Whales has its own dialect and closely-related families share calls. We know this because biologists have begun to categorize the complex calls of Killer Whales and to try and understand what they mean. We are attempting to decipher even more of these Killer Whale ‘words’ and are also throwing in several thousand Pilot Whales calls too.

To join in you just visit whale.fm and listen to the large, main call. An array of computer-identified, smaller calls are shown and you have to pick the one that sound most like it. By pairing up all the best-matches we hope to begin to create a web of similar sounds and see the web of ‘words’ these whales are using to communicate.

Whales and dolphins have very sophisticated hearing sensory organs and can produce loud sounds that they use for communication, orientation and foraging under water. Biologists can listen to the sounds that whales and dolphins produce by putting microphones under water (so-called ‘hydrophones’). Many of the calls that you will encounter on this site have been recorded from animals that were tagged using ‘D-Tags’. These are non-invasive tags that are attached to the whales using suction-cups, which eventually fall off. They also allow us to use GPS to track the Whales as they move around.

Don’t forget you can ask questions and make comments on out Whale Talk site and also find us on Twitter and Facebook.

[Cross-posted with the new Whale FM blog]

We’re inviting you – for a limited time only! – to take part in a big experiment! For our first ‘Zooniverse Lab’, we’ve partnered with NASA, who are training astronauts in an underwater environment. For the next two weeks they’re sending six astronauts, researchers and habitat technicians to live in an undersea habitat and work as part of the NASA Extreme Environment Mission Operations (NEEMO). We’re interested to see if having many eyes on the problem will help the scientists and engineers working on NEEMO.

The mission is taking place 43 feet underwater at the NOAA ‘Aquarius’ facility, three miles off the coast of Key Largo, USA. The goal of this NEEMO-15 mission is to understand how NASA may one day explore and operate on asteroids, using techniques that are orders of magnitude more capable and efficient than methods are in use today.

For the Zooniverse this is the first of a new breed of project for us – one where the experiment is the interface itself! The project will only run for two weeks and in that time we hope to collect sufficient data to work out if an interface where people confirm or reject each other’s classifications can prove more efficient than our current approach of purely independent classification. NASA science teams will be using the data collected during NEEMO-15, alongside your classifications, to help develop different data sampling techniques for future asteroid missions.

Although we can’t promise that this project will result in academic papers, it will aid the NEEMO project and we’re convinced that it can help us better understand the limits of citizen science online.

Check out http://neemo.zooniverse.org and let us know what you think.