Tag Archives: Zooniverse

A New Paper All About #yellowballs

PIA18909_fig1

There is a new Milky Way Project paper in the news today, concerning the #yellowballs that were found by Milky Way Project volunteers.

The Yellowballs appeared on the very first day of the Milky Way Project when user kirbyfood asked ‘what is this?’ and I wasn’t sure so jokingly called it a ‘#yellowball’, since that’s what is looked like. We use hashtags on talk.milkywayprojct.org, and that user, and many others, went off and tagged hundreds of the things over the next few months. Before we knew it there was a catalogue of nearly 1,000 of them. However, we still didn’t know what they really were, and so Grace Wolf-Chase, Charles Kerton, and other MWP collaborators have put a lot of effort into figuring it out. From the JPL press release:

So far, the volunteers have identified more than 900 of these compact yellow features. The next step for the researchers is to look at their distribution. Many appear to be lining the rims of the bubbles, a clue that perhaps the massive stars are triggering the birth of new stars as they blow the bubbles, a phenomenon known as triggered star formation. If the effect is real, the researchers should find that the yellow balls statistically appear more often with bubble walls.

This new paper is the fourth from the Milky Way Project, and adds to the Zooniverse’s growing list of 80+ publications made possible thanks to our amazing volunteers. You can see the complete set at zooniverse.org/publications.

The full list of volutneers who helped tag the yellowballs is shown below. Each and everyone one of you made a valuable contribution to this paper. Thank you to everyone who helped in this search!

KhalilaRedBird, lpspieler, greginak, LarryW, chelseanr, broomrider1970, Dealylama, Cruuux, Mirsathia, suelaine, sdewitt, stukii, kmasterdo, PattyD, HeadAroundU, Fezman92, Jakobswede, Jk478B27Ds395, Kerry_Wallis, iacomo, Ken Koester, ttfnrob, jules, Falconet, Caidoz13, Starsheriff, ascil, simonron, tyna_anna, gwolfchase, Greendragon00, Ranchi, kirbyjp, githensd, katieofoz, harbinjer, ycaruth1, embo, echong, Feylin, stock_footage, zookeeper, joke slayer, karvidsson, Furiat, Tyler Reynolds, Manjingos, cathcollins, legoeeyore, GabyB, eshafto, mtparrish, 59Vespa, amatire, TheScribblery, pschmal, Helice, norfolkharryuk, WilB, jamesw40k, koenvisser, dragonjools, Nocterror, nunyaB, hansbe, meheler, Cahethel, Alice, stellar190, mabbenson, Embyrr922, gnome_king, jumpjet2k, tchan, yoman93, and Loulouuse.

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Combining Your Clicks with Milkman

I’ve been building a new app for the Milky Way Project called Milkman. It goes alongside Talk and allows you to see where everyone’s clicks go, and what the results of crowdsourcing look like. It’s open source, and a good step toward open science. I’d love feedback from citizen scientists and science users alike.

Milkman

Milkman is so called because it delivers data for the Milky Way Project, and maybe eventually some other Zooniverse projects too. You can access Milkman directly at explore.milkywayproject.org (where you can input a Zooniverse subject ID or search using galactic coordinates), or more usefully, you can get to Milkman via Talk – using the new ‘Explore’ button that now appears for logged-in users.

Clicking ‘Explore’ will show you the core view of Milkman: a display of all the clicks from all the volunteers who have seen that image and the current, combined results.

Screenshot 2014-09-09 09.14.38

Milkman 2

Milkman is a live, near-realtime view of the state of the science output from the current Milky Way Project. It might help people discussing items on Talk to understand what other objects are in the MWP images, and it hopefully shows how volunteers’ clicks are used.

Milkman uses a day-old clone of the main Zooniverse database, which means the clicks are at most 24 hours old. The clustering is performed using a technique called DBSCAN, which takes the vast array of clicks on each image and tries to automatically group them up. The resultant, averaged bubbles, EGOs, clusters, and galaxies are often better than any individual drawing, showing the power of crowdsourcing in acton.

Milkman is open source on GitHub and I’m happy to accept issues and feedback through the repo’s issues.

Immediate plans for Milkman include a navigable map on the homepage (to let you explore the whole galaxy), better links to other public astronomical data, and access to the current state of the reduced MWP2 catalogue as a whole. If you have ideas or requests either contact me or create an issue on GitHub.

New MWP paper outlines the powerful synergy between citizen scientists, professional scientists, and machine learning

bubble_gallery_sorted_v2

A new Milky Way Project paper was published to the arXiv last week. The paper presents Brut, an algorithm trained to identify bubbles in infrared images of the Galaxy.

Brut uses the catalogue of bubbles identified by more 35,000 citizen scientists from the original Milky Way Project. These bubbles are used as a training set to allow Brut to discover the characteristics of bubbles in images from the Spitzer Space Telescope. This training data gives Brut the ability to identify bubbles just as well as expert astronomers!

The paper then shows how Brut can be used to re-assess the bubbles in the Milky Way Project catalog itself, and it finds that more than 10% of the objects in this catalog are really non-bubble interlopers. Furthermore, Brut is able to discover bubbles missed by previous searches too, usually ones that were hard to see because they are near bright sources.

At first it might seem that Brut removes the need for the Milky Way Project –  but the ruth is exactly the opposite. This new paper demonstrates a wonderful synergy that can exist between citizen scientists, professional scientists, and machine learning. The example outlined with the Milky Way Project is that citizens can identify patterns that machines cannot detect without training, machine learning algorithms can use citizen science projects as input training sets, creating amazing new opportunities to speed-up the pace of discovery. A hybrid model of machine learning combined with crowdsourced training data from citizen scientists can not only classify large quantities of data, but also address the weakness of each approach if deployed alone.

We’re really happy with this paper, and extremely grateful to Chris Beaumont (the study’s lead author) for his insights into machine learning and the way it can be successfully applied to the Milky Way Project. We will be using a version of Brut for our upcoming analysis of the new Milky Way Project classifications. It may also have implications for other Zooniverse projects.

If you’d like to read the full paper, it is freely available online at at the arXiv – and Brut can found on GitHub.

The Project Is Complete… But Not For Long

After a fantastic (re)launch in December and a busy January, the Milky Way Project was doing well and was about 93% complete… until about 8 hours ago. Last night, the social media powerhouse that is IFLS pointed tens of thousands of people our way and in an hour they finished the project. This is obviously great news for science but some people might be wondering what happens next. 

MWP

The good news is that we have more data! The bad news is that it won’t be ready for another few weeks. In the meantime we are also working on producing some results from all your work, and you can continue to discuss things on Talk. We’ll let everyone know when we have more images to classify but for now: thank you for all your hard work and attention.

We shall return!

New Milky Way Project Poster

I’ve been diving into the bubbles database recently and ended up creating cutouts of all 3,744 large bubbles from the DR1 data release. From there it was an easy enough job to create this new Milky Way Project poster. It uses all 3,744 bubbles at least once (several are used more than once).

MWP Logo Mosaic of Bubbles

I’m currently working on three new Milky Way Project papers and will be blogging about them in the next weeks and months.

The Bubbling Galactic Disk

Some of the most beautiful structures in Spitzer GLIMPSE data are the bubbles. Bubbles are regions of gas, usually found around newly formed stars, often with shells of material surrounding them (the green 8 μm emission above). These appear as rings in the GLIMPSE images and can vary in appearance from strikingly prominent to intriguingly faint. They can be anything from complete circles and ellipses, to fractured, fragmented remains.

As part of Project IX we’re going to ask you to find and measure these bubbles. Researchers can use this information to learn a lot about how these objects form and how they trigger star formation.

RCW120

Above is an image of RCW 120, the titual “perfect bubble” from a 2009 paper by Deharveng, Zavagno, Schuller, Caplan, Pomarès and De Breuck. This colour-composite image shows Hα emission in blue, 8 μm emission in green and the 24 μm emission of small dust grains in red. The image is approximately 24′ degrees wide.

The green material has been swept up as the region expanded, after the formation of a massive star in the centre. There are about 2000 Solar masses of neutral material here, and this has fragmented into lumps. This is where star formation is occurring. The authors of the study found 138 potential star-forming objects in the ring around RCW 120.

In 2006, a group of astronomers visually inspected the GLIMPSE data for bubbles and catalogued their results in a paper titled ‘The Bubbling Galactic Disk‘. I’m a sucker for a great paper title. The team behind this study has been looking at the GLIMPSE data ever since. As mentioned above, bubbles are important features in the study of star formation. Here’s how they are described in ‘The Bubbling Galactic Disk‘:

The study of bubbles gives information about the stellar winds that produce them and the structure and physical properties of the ambient ISM – interstellar medium – into which they are expanding. Additional physical insights include the hydrodynamics of gas and dust in expanding bubbles, the impact of expanding bubbles on magnetic fields in the diffuse ISM, and mass-loss rates during the evolution of stars.

In 2006 322 bubbles were visually identified by just a handful of people. Since that time two things have changed. Firstly, there is now a lot more data, and therefore more bubbles. Spitzer has also continued to map more of the galactic plane for the GLIMPSE360 project – more on that in a later post. Secondly, the Zooniverse now exists!

Everytime the Zooniverse and bubbles have been mentioned together, someone has been there saying that we should get the public to find and measure them. Whether this is between Chris, myself and others at Zooniverse HQ or between Grace Wolf-Chase at Adler Planetarium and various members of the ‘The Bubbling Galactic Disk‘ study. Bubbles and the Zooniverse should be a match made in the heavens.

Why are bubbles such a good target? For many reasons. They are not only amazing to look at, but also are numerous in the GLIMPSE data. They are tricky to measure but not impossibly hard. They are scientifically valuable objects to catalogue and measure the properties of, and they require more than one independent, human measurement to get a good handle on – this is key of course.

Many of the folks behind the ‘The Bubbling Galactic Disk‘ are part of the Project IX science team. We hope that everyone out there in the Zooniverse community can help refine and expand the existing bubble catalogue as part of Project IX. With the addition of new data, we also hope to find many new bubbles.

We are currently developing the bubble tool – the first user interface portion of the Project IX site  – which will have similarities to the Moon Zoo crater tool. We hope to be able to share it with you all soon so that you can help us to test and refine it. It is exciting to be able to involve everyone at this early stage.

If you’re interested in following this project and its take on bubbles, I’d suggest reading ‘The Bubbling Galactic Disk‘ and looking at the GLIMPSE website. If you have any questions – let us know. Bubble are just one thing we can see in the GLIMPSE data. More posts will follow about other scientifically useful objects lurking in this amazing infrared archive.