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Moon NASA Space Science

Citizen Scientists Help Explore the Moon 60

Pickens writes "NPR reports that NASA's Lunar Reconnaissance Orbiter is doing such a good job photographing every bit of the moon's surface that scientists can't keep up, so Oxford astrophysicist Chris Lintott is asking amateur astronomers to help review, measure, and classify tens of thousands of moon photos streaming to Earth using the website Moon Zoo, where anyone can log on, get trained, and become a space explorer. 'We ask people to count the craters that they can see ... and that tells us all sorts of things about the history and the age of that bit of surface,' says Lintott. Volunteers are also asked to identify boulders, measure the craters, and generally classify what is found in the images. If one person does the classification — even if they're an expert — then anything odd or interesting can be blamed on them. But with multiple independent classifications, the team can statistically calculate the confidence in the classification. That's a large part of the power of Moon Zoo. Lintott adds the British and American scientists heading up the LRO project have been randomly checking the amateur research being sent in and find it as good as you would get from an expert. 'There are a whole host of scientists ... who are waiting for these results, who've already committed to using them in their own research.'"
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Citizen Scientists Help Explore the Moon

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  • What's the chance that volunteers will "discover" that the man in the moon is actually Colbert?

  • by arthurpaliden ( 939626 ) on Monday May 24, 2010 @09:11PM (#32331372)
    Now we will able to see all the alien moon bases before NASA and their NWO friends have a chance to PhotoShop them out.
  • Would they put my name as a coauthor of the papers? Yes? Deal!
    • by kaitos ( 185784 )

      They select 50 random contributers as coauthors for papers.

  • Mutual Benefit (Score:3, Insightful)

    by QuantumG ( 50515 ) * <qg@biodome.org> on Monday May 24, 2010 @09:18PM (#32331436) Homepage Journal

    From the faq (http://www.moonzoo.org/faq):

    Q: What happens to the classifications I provide?

    A: They're stored with those provided by everyone who comes to Moon Zoo. The Moon Zoo team will carefully analyse the results to make sure that collectively we're producing results that are useful to scientists -- keep an eye on the Moon Zoo blog for details. All results will eventually be made public for anyone to use.

    I think the problem here is that it is all take and no give. Categorize our images for us! We'll give you the data "eventually". Crazy idea, how about doing the statistical correlation of multiple contributors in realtime and display that information on an overall map of the Moon so there's some sense of progress at the task.

    • by Zakabog ( 603757 )

      Crazy idea, how about doing the statistical correlation of multiple contributors in realtime and display that information on an overall map of the Moon so there's some sense of progress at the task.

      Sure sounds good in theory but it's much easier to have a bunch of people skew the results if they're posted in real time. Imagine the Colbert Report picking up on this and deciding to tell the viewers to classify every crater as being Stephen Colbert's age... It'd make the automated process much harder and they'll have to spend much more time combing the skewed results.

    • Re:Mutual Benefit (Score:5, Insightful)

      by Gadget_Guy ( 627405 ) * on Monday May 24, 2010 @10:22PM (#32331822)

      I think the problem here is that it is all take and no give. Categorize our images for us! We'll give you the data "eventually".

      It sounds a bit childish, really. How can you say it is all take and no give, and then immediately say that they WILL be giving you the results, but only after it has gone through that pesky scientific process.<WHINE>But I want it now!</WHINE>

      What is the problem with waiting for the right answer? Zakabog has already pointed out that a real time display could be used maliciously, but it could even skew the results by well-intentioned people. If the first person who submits a result for a given region makes a mistake, then the next person who analyses that region might compare their results with the first and "correct" their own mistake. If you use statistics to build confidence in the results then the last thing you should do is tell the subjects what you are currently expecting them to do. That only uses statistics to compound errors.

      • Re: (Score:3, Interesting)

        Comment removed based on user account deletion
        • Because it is basic game theory? You want the little hamster to continue running around the little wheel you give him a cookie to work for. If he gets little nibbles of the cookie he'll work HARDER trying to get more cookie, thus giving you more work. Hell nobody is saying they have to give them the actual recorded data in real time, just throw the monkey a reward for pushing the button. Maybe something that ONLY shows how you are doing? Surely that would discourage the cranks while giving the hamster a reason to keep running the wheel.

          Galazy Zoo [galaxyzoo.org], which pioneered this kind of crowd-sourced classification, seems to disprove that need. Most of the people are astronomy fans, and the joy of looking at raw telescope pictures was reward enough. Eventually they did add a list of previously viewed galaxies, and let you mark your favorites for later viewing. Besides, it had 250,000 users. Get each person to look at 20 galaxies on average (just a few minutes time, easy to do) and you have 5 people looking at each of 1 million galaxies.

          In othe

    • Aside from the other respondents showing issues with this idea, I can tell you that with the Solar Stormwatch program they run, our data was compiled and recognized sooner than I was expecting (my participation, along with over 210 other collaborators, confirmed seven CMEs).

  • by macraig ( 621737 ) <mark DOT a DOT craig AT gmail DOT com> on Monday May 24, 2010 @09:37PM (#32331576)

    Maybe they learned this from the distributed computing folks? SETI@Home and World Community Grid take advantage of the same process.

    • Maybe they learned this from the distributed computing folks?

      More likely they learned it from the Galaxy Zoo [galaxyzoo.org] folks.

      • Re: (Score:3, Insightful)

        by macraig ( 621737 )

        How long has GalaxyZoo been around? Longer than SETI@Home? It's more likely both projects took the hint from how SETI@Home processes data. As another commenter correctly pointed out, these two projects do with spare eyes and brain cycles what SETI@Home does with spare CPU cycles, and all of them rely on having multiple redundant results for the same dataset to verify integrity of the result. It's not exactly rocket science to figure out such a technique would be useful, but SETI@Home has been around for

    • I do the same thing occasionally with GalaxyZoo (www.galaxyzoo.org). After being trained you classify galaxies. The second version is much better than the first iteration and goes into more detail. I like the "progress indicator" idea in the post above, but see no practical way for it to work.
    • Yep. Except instead of putting spare CPU cycles to work like SETI@Home, Boinc, etc., the Zooniverse projects put spare user cycles to useful work.

      I many times enjoyed getting a buzz and staring at mind staggeringly distant galaxies [galaxyzoo.org] for an hour or two, with some freakishly talented electric guitarists [blogspot.com] providing some recorded accompaniment. While I consider it "down time," my friends the astronomers consider it useful work.

  • I think I found an important rock! Oh wait, it just a regular rock. Nevermind.
  • by pongo000 ( 97357 ) on Monday May 24, 2010 @10:03PM (#32331724)

    ...would be to use the statistically-validated user input in a feed-forward image recognition neural network utilizing error feedback that would "learn" to identify the various features of interest. Use edge detection to identify the features of interest (for instance, by number just like a paint-by-number canvas), and have users "identify" what they see. We're talking about invariant scale here, which vastly simplifies the learning process as well as automated feature measurement.

    I was doing this in the '90s using multi-band spectral imagery from LANDSAT with good success. I would imagine there have been some advances in this area since that time.

    • by FleaPlus ( 6935 )

      ...would be to use the statistically-validated user input in a feed-forward image recognition neural network utilizing error feedback that would "learn" to identify the various features of interest. Use edge detection to identify the features of interest (for instance, by number just like a paint-by-number canvas), and have users "identify" what they see. We're talking about invariant scale here, which vastly simplifies the learning process as well as automated feature measurement.

      I was doing this in the '90s using multi-band spectral imagery from LANDSAT with good success. I would imagine there have been some advances in this area since that time.

      Actually, since the '90s people have largely switched from using neural nets to support vector machines [wikipedia.org] (or maybe a restricted Boltzmann machine [wikipedia.org]). ;) I do agree that it'd be an interesting training set for a machine learning algorithm, though.

    • You'd think that would be the case, but there are several reasons why humans are a better solution to this than a computer program:

      1. Recognition like this requires complex interpretation. Computers might be able to interpret them, but you have no way of validating that interpretation, and computers are pretty literal about it anyway. Multiple humans with cross-checked results are going to give you (by and large) more accurate results. If we can't manage it with OCR of clearly-written and cleanly-scanne

      • Drat, I managed to reply to the wrong post, thereby partly disproving my own theory about the accuracy of humans. ;)

        This was meant to be in reply to "Crazy idea..." below.

  • Why not just use a computer to count craters? The current algorithms for optical recognition should work rather well for 'find circles'. Not that it's nice that they're involving us normal folk in their fancy science, but this is the sort of mundane task that computers are made for....
    • Re:Crazy idea.... (Score:5, Informative)

      by war4peace ( 1628283 ) on Monday May 24, 2010 @10:37PM (#32331904)
      You might want to check out some of those pictures before jumping in with speculations.
      Craters are being lit from various dirns, depending on the latitude, longitude and Sun position. This sort of imagery needs a human mind to correctly process it. Furthermore, it's not only about "counting craters", but identifying other interesting features (such as crater bouldery, artificial structures, linear features, moulds and so on). Plus, images have varying degrees of clearness (I found some corrupt images as well, pity you can't report them). The "Boulder Wars" minigame itself is rather interesting too.
      • by QuantumG ( 50515 ) *

        And you'll note that every image has already been tagged with each of those variables, so all you need to do is train a model for each.

  • ...these citizens could spend their time volunteering their time and skills in their community and actually make a fellow human's life better on this planet. While this might be a good ploy to pique the interest of some students, I'm trying to figure out how this effort won't be moot in a few years when the computer image recognition/analysis software can do the same task much more efficiently.

    • Re: (Score:2, Insightful)

      And how often does volunteering actually end up really helping people in the long term?

      There aren't too many opportunities to teach skills which will help people to actually get ahead.

      Such things I'd support, but all "volunteering" has turned into is just giving handouts, these don't help humanity but rather hinder progress.
    • Free help is pretty effective. You're helping to educate the public. You're involving the public in the resulting science. This is a very smart way of doing things. Based on your attitude we should wait on doing anything useful until our machine overlords are here and doing it for us, doh!

  • by plopez ( 54068 ) on Monday May 24, 2010 @10:55PM (#32332016) Journal

    This is exactly the sort of mind numbing work grad students should be doing for a pittance. This will put them out of work! We are not providing the right incentives to create our next generation of scientists.

    (that was supposed to be humor)

  • FTA:

    And why not use computers? Lintott says they can only identify what they are programmed to look for, and might miss the unusual. "Computers don't make discoveries," he says. "They don't point at the thing in the corner and ask the question: What's that?"

    Computers can however, identify what they are programmed to look for, and then indicate any areas which have features which they do not recognise. At the very least he should write a filter to parse out the completely typical images before getting the general public to do his work for him.
    This guy is either too lazy or cheap to write some image analysis software, or a luddite who doesn't trust computers.

  • Moon Zoo is one of many projects on http://www.zooniverse.org/ [zooniverse.org]

    It's a great way to learn about the various images/data being captured, both in our solar system and beyond, while actually contributing something to the scientific community. There is something extremely exciting about watching a clip of the sun and seeing a comet appear out of nowhere and zoom around the sun with its tail pointing away. Or being among the first to notice a new solar storm which might affect astronauts in orbit. Or spotting
  • I created a required Zooniverse account in order to try out the Moon Zoo. New Zooniverse accounts have "show email" and "receive newsletters" automatically enabled by default. Shame on them.
  • Is that Roger Waters on The Dark Side of the Moon?

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