This coming Saturday 13th April is Citizen Science Day, an ‘annual event to celebrate and promote all things citizen science’. Here at the Zooniverse, one of our team members will be posting each day this week to share with you their favourite Zooniverse projects. Today’s post is from Grant Miller, project manager of the Zooniverse team at the University of Oxford.
Having been at the Zooniverse for almost six years and helped over one hundred research teams launch their project on the Zooniverse platform I find it very difficult to choose just one of them as my favourtie. However, unlike Helen did on Tuesday, I’m going to give it a try 😛
For me it’s got to be the very first project that was pitched to me on my first day of the job back in 2013 – Penguin Watch! Over the last decade the lead researcher Tom Hart and his team have been travelling to the Southern Ocean and Antarctica to place time-lapse cameras looking at penguin nests. They now collect so many images each year the cannot do their science without the help of the Zooniverse crowd. This projecy perfectly demonstrates the key elements which go into making a truly great citizen science project:
It has a clear and relatable research goal: Help count penguins so we can understand how over-fishing and climate change is affecting their populations, and then use that information to influence policy makers.
It has an extremely simple task that for now can only be done accurate by human eyes: Click on the penguins in the image. It’s so simple we have 4-year-old children helping their parents do it!
It has an amazing and engaged research team and volunteer community: Even though they are a very small team the scientists take plenty of time to communicate with their volunteer community via the Talk area of the project, newsletters, and social media channels. There is also a fantastic core group of volunteer moderators who put in so much effort to make sure the project is running as well as it should.
In addition to all of this I was lucky enough to join them on one of their Antarctic expeditions last year, as they went down to maintain their time-lapse cameras and collect the data that goes into Penguin Watch. You can see my video diary (which I’m posting once per day on the run up to World Penguin Day on the 25th April) at daily.zooniverse.org.
The team behind the Exoplanet Explorers project has just published a Research Note of the American Astronomical Society announcing the discovery of 28 new exoplanet candidates uncovered by Zooniverse volunteers taking part in the project.
Nine of these candidates are most likely rocky planets, with the rest being gaseous. The sizes of these potential exoplanets range from two thirds the size of Earth to twice the size of Neptune!
This post is by Adina Feinstein. Adina is a graduate student at the University of Chicago. Her work focuses on detecting and characterizing exoplanets. Adina became involved with the Exoplanet Explorers project through her mentor, Joshua Schlieder, at NASA Goddard through their summer research program.
Let me tell you about the newly discovered system – K2-288 – uncovered by volunteers on Exoplanet Explorers.
K2-288 has two low-mass M dwarf stars: a primary (K2-288A) which is roughly half the size of the Sun and a secondary (K2-288B) which is roughly one-third the size of the Sun. The capital lettering denotes a star in the planet-naming world. Already this system is shaping up to be pretty cool. The one planet in this system, K2-288Bb, hosts the smaller, secondary star. K2-288Bb orbits on a 31.3 day period, which isn’t very long compared to Earth, but this period places the planet in the habitable zone of its host star. The habitable zone is defined as the region where liquid water could exist on the planet’s surface. K2-288Bb has an equilibrium temperature -47°C, colder than the equilibrium temperature of Earth. It is approximately 1.9 times the radius of Earth, which places it in a region of planet radius space where we believe planets transition to volatile-rich sub-Neptunes, rather than being potentially habitable super-Earth. Planets of this size are rare, with only about a handful known to-date.
The story of the discovery of this system is an interesting one. When two of the reaction wheels on the Kepler spacecraft failed, the mission team re-oriented the spacecraft to allow observations to continue to happen. The re-orientation caused slight variations in the shape of the telescope and temperature of the instruments on board. As a consequence, the beginning of each observing campaign experienced extreme systematic errors and initially, when searching for exoplanet transits, we “threw out” or ignored the first days of observing. Then, when we were searching the data by-eye for new planet candidates, we came across this system and only saw 2 transits. In order for follow-up observations to proceed, we need a minimum of 3 transits, so we put this system on the back-burner. The light curve (the amount of light we see from a star over time) with the transits is shown below.
Later, we learned how to model and correct for the systematic errors at the beginning of each observing run and re-processed all of the data. Instead of searching it all by-eye again, as we had done initially, we outsourced it to Exoplanet Explorers and citizen scientists, who identified this system with three transit signals. The volunteers started a discussion thread about this planet because given initial stellar parameters, this planet would be around the same size and temperature as Earth. This caught our attention. As it turns out, there was an additional transit at the beginning of the observing run that we missed when we threw out this data! Makennah Bristow, a fellow intern of mine at NASA Goddard, identified the system again independently. With now three transits and a relatively long orbital period of 31.3 days, we pushed to begin the observational follow-up needed to confirm this planet was real.
First, we obtained spectra, or a unique chemical fingerprint of the star. This allowed us to place better constraints on the parameters of the star, such as mass, radius, temperature, and brightness. While obtaining spectra from the Keck Observatory, we noticed a potential companion star. We conducted adaptive optics observations to see if the companion was bound to the star or a background source. Most stars in the Milky Way are born in pairs, so it was not too surprising that this system was no different. After identifying a fainter companion, we made extra sure the signal was due to a real planet and not the companion; we convinced ourselves this was the case.
Finally, we had to determine which star the planet was orbiting. We obtained an additional transit using the Spitzer spacecraft. Using both the Kepler and Spitzer transits, we derived planet parameters for both when the planet orbits the primary and the secondary. The planet radius derived from both light curves was most consistent when the host star was the secondary. Additionally, we derived the stellar density from the observed planet transit and this better correlated to the smaller secondary star. To round it all off, we calculated the probability of the signal being a false positive (i.e. not a planet signal) when the planet orbits the secondary and it resulted in a false positive probability of roughly 10e-9, which indicates it most likely is a real signal.
The role of citizen scientists in this discovery was critical, which is why some of the key Zooniverse volunteers are included as co-authors on this publication. K2-288 was observed in K2 Campaign 4, which ran from April to September back in 2015. We scientists initially missed this system and it’s likely that even though we learned how to better model and remove spacecraft systematics, it would have taken years for us to go back into older data and find this system. Citizen scientists have shown us that even though there is so much new data coming out, especially with the launch of the Transiting Exoplanet Survey Satellite, the older data is still a treasure trove of new discoveries. Thank you to all of the Exoplanet volunteers who made this discovery possible and continue your great work!
The paper written by the team is available here. It should be open to all very shortly.
This is the first of two guest posts from the Exoplanet Explorers research team announcing two new planets discovered by their Zooniverse volunteers. This post was written by Jessie Christiansen.
Hello citizen scientists! We are here at the 233rd meeting of the American Astronomical Society, the biggest astronomy meeting in the US of the year (around 3000 astronomers, depending on how many attendees are ultimately affected by the government shutdown). I’m excited to share that on Monday morning, we are making a couple of new exoplanet announcements as a result of your work here on Zooniverse, using the Exoplanet Explorers project!
Last year at the same meeting, we announced the discovery of K2-138. This was a system of five small planets around a K star (an orange dwarf star). The planets all have very short orbital periods (from 2.5 to 12.8 days! Recall that in our solar system the shortest period planet is Mercury, with a period of ~88 days) that form an unbroken chain of near-resonances. These resonances offer tantalizing clues as to how this system formed, a question we are still trying to answer for exoplanet systems in general. The resonances also beg the question – how far could the chain continue? This was the longest unbroken chain of near first-order resonances which had been found (by anyone, let alone citizen scientists!).
At the time, we had hints of a sixth planet in the system. In the original data analysed by citizen scientists, there were two anomalous events that could not be accounted for by the five known planets – events that must have been caused by at least one, if not more, additional planets. If they were both due to a single additional planet, then we could predict when the next event caused by that planet would happen – and we did. We were awarded time on the NASA Spitzer Space Telescope at the predicted time, and BOOM. There it was. A third event, shown below, confirming that the two previous events were indeed caused by the same planet, a planet for which we now knew the size and period.
So, without further ado, I’d like to introduce K2-138 g! It is a planet just a little bit smaller than Neptune (which means it is slightly larger than the other five planets in the system, which are all between the size of Earth and Neptune). It has a period of about 42 days, which means it’s pretty warm (400 degrees K) and therefore not habitable. Also, very interestingly, it is not on the resonant chain – it’s significantly further out than the next planet in the chain would be. In fact, it’s far enough out that there is a noticeable gap – a gap that is big enough to hide more planets on the chain. If these planets exist, they don’t seem to be transiting, but that doesn’t mean they couldn’t be detected in other ways, including by measuring the effect of their presence on the other planets that do transit. The planet is being published in a forthcoming paper that will be led by Dr Kevin Hardegree-Ullman, a postdoctoral research fellow at Caltech/IPAC.
In the meantime, astronomers are still studying the previously identified planets, in particular to try to measure their masses. Having tightly packed systems that are near resonance like K2-138 provides a fantastic test-bed for examining all sorts of planet formation and migration theories, so we are excited to see what will come from this amazing system discovered by citizen scientists on Zooniverse in years to come!
We are also announcing a second new exoplanet system discovered by Exoplanet Explorers, but I will let Adina Feinstein, the lead author of that paper, introduce you to that exciting discovery.
We recently uncovered a couple of bugs in the Zooniverse code which meant that the wrong question text may have been shown to some volunteers on Zooniverse projects while they were classifying. They were caught and a fix was released the same day on 29th November 2018.
The bugs only affected some projects with multiple live workflows from 6th-12th and 20th-29th November.
One of the bugs was difficult to recreate and relied on a complex timing of events, therefore we think it was rare and probably did not affect a significant fraction of classifications, so it hopefully will not have caused major issues with the general consensus on the data. However, it is not possible for us to say exactly which classifications were affected in the timeframe the bug was active.
We have apologised to the relevant science teams for the issues this may cause with their data analysis, but we would also like to extend our apologies to all volunteers who have taken part in these projects during the time the bugs were in effect. It is of the utmost importance to us that no effort is wasted on our projects and when something like this happens it is taken very seriously by the Zooniverse team. Since we discovered these bugs we worked tirelessly to fix them, and we have taken actions to make sure nothing like this will happen in the future.
We hope that you accept our most sincere apologies and continue the amazing work you do on the Zooniverse. If you have any questions please don’t hesitate to contact us at email@example.com.
Hi all, I am Coleman Krawczyk and for the past year I have been working on tools to help Zooniverse research teams work with their data exports. The current version of the code (v1.3.0) supports data aggregation for nearly all the project builder task types, and support will be added for the remaining task types in the coming months.
What does this code do?
This code provides tools to allow research teams to process and aggregate classifications made on their project, or in other words, this code calculates the consensus answer for a given subject based on the volunteer classifications.
The code is written in python, but it can be run completely using three command line scripts (no python knowledge needed) and a project’s data exports.
The first script is the uses a project’s workflow data export to auto-configure what extractors and reducers (see below) should be run for each task in the workflow. This produces a series of `yaml` configuration files with reasonable default values selected.
Next the extraction script takes the classification data export and flattens it into a series of `csv` files, one for each unique task type, that only contain the data needed for the reduction process. Although the code tries its best to produce completely “flat” data tables, this is not always possible, so more complex tasks (e.g. drawing tasks) have structured data for some columns.
The final script takes the results of the data extraction and combine them into a single consensus result for each subject and each task (e.g. vote counts, clustered shapes, etc…). For more complex tasks (e.g. drawing tasks) the reducer’s configuration file accepts parameters to help tune the aggregation algorithms to best work with the data at hand.
At the moment this code is provided in its “offline” form, but we testing ways for this aggregation to be run “live” on a Zooniverse project. When that system is finished a research team will be able to enter their configuration parameters directly in the project builder, a server will run the aggregation code, and the extracted or reduced `csv` files will be made available for download.
Occasionally we run studies in collaboration with external researchers in order to better understand our community and improve our platform. These can involve methods such as A/B splits, where we show a slightly different version of the site to one group of volunteers and measure how it affects their participation, e.g. does it influence how many classifications they make or their likelihood to return to the project for subsequent sessions?
One example of such a study was the messaging experiment we ran on Galaxy Zoo. We worked with researchers from Ben Gurion University and Microsoft research to test if the specific content and timing of messages presented in the classification interface could help alleviate the issue of volunteers disengaging from the project. You can read more about that experiment and its results in this Galaxy Zoo blog post https://blog.galaxyzoo.org/2018/07/12/galaxy-zoo-messaging-experiment-results/.
As the Zooniverse has different teams based at different institutions in the UK and the USA, the procedures for ethics approval differ depending on who is leading the study. After recent discussions with staff at the University of Oxford ethics board, to check our procedure was up to date, our Oxford-based team will be changing the way in which we gain approval for, and report the completion of these types of studies. All future study designs which feature Oxford staff taking part in the analysis will be submitted to CUREC, something we’ve been doing for the last few years. From now on, once the data gathering stage of the study has been run we will provide all volunteers involved with a debrief message.
The debrief will explain to our volunteers that they have been involved in a study, along with providing information about the exact set-up of the study and what the research goals were. The most significant change is that, before the data analysis is conducted, we will contact all volunteers involved in the study allow a period of time for them to state that they would like to withdraw their consent to the use of their data. We will then remove all data associated with any volunteer who would not like to be involved before the data is analysed and the findings are presented. The debrief will also contain contact details for the researchers in the event of any concerns and complaints. You can see an example of such a debrief in our original post about the Galaxy Zoo messaging experiment here https://blog.galaxyzoo.org/2015/08/10/messaging-test/.
As always, our primary focus is the research being enabled by our volunteer community on our individual projects. We run experiments like these in order to better understand how to create a more efficient and productive platform that benefits both our volunteers and the researchers we support. All clicks that are made by our volunteers are used in the science outcomes from our projects no matter whether they are part of an A/B split experiment or not. We still strive never to waste any volunteer time or effort.
We thank you for all that you do, and for helping us learn how to build a better Zooniverse.
Zooniverse team members based at Chicago’s Adler Planetarium celebrated Earth Day this weekend at Earthfest, a two-day-long celebration of the planet we call home.
In addition to many activities for all ages throughout the museum, museum visitors were able to speak with Zooniverse team members to learn about the many earth-related projects available online and on the app. Visitors could also participate in a real-life version of Floating Forests, in which they used tracing paper to illustrate areas of kelp forests on a satellite image. The activity demonstrated how Zooniverse researchers use aggregation to combine many classifications into one very accurate result. Stay tuned for the results of those tracings, coming soon!
Zooniverse team members also had some help from our friends at the Field Museum, who stopped by to talk about Microplants, a Zooniverse project studying some of the earliest land plants in the liverwort genus Frullania.
We love speaking with museum visitors and sharing the excitement of participating in real citizen science projects. If you’re in the Chicago area and missed us last weekend, keep an eye out for more information about the Adler Planetarium’s spring Members’ Night, when we’ll have even more fun Zooniverse-related activities for you!
Irma has brought widespread devastation to many islands in the Caribbean over the last few days, and now Hurricane Jose is a growing threat in the same region.
By analysing images of the stricken areas captured by ESA’s Sentinel-2 satellites, Zooniverse volunteers can provide invaluable assistance to rescue workers. Rescue Global are a UK-based disaster risk reduction and response charity who are deploying a team to the Caribbean and will use the information you provide to help them assess the situation on the ground.
We’re testing out a new feature of our interface, which means if you’re classifying images on Comet Hunters you may see occasional pop-up messages like the one pictured above.
The messages are designed to give you more information about the project. If you do not want to see them, you have the option to opt-out of seeing any future messages. Just click the link at the bottom of the pop-up.
You can have a look at this new feature by contributing some classifications today at www.comethunters.org.