Getting Black Hole Hunters ready for launch
24 September 2021, by Adam McMaster in Black Hole Hunters
Our upcoming project, Black Hole Hunters, recently went through the Zooniverse beta review process. Thanks to everyone who took the time to review the project! We received a lot of useful feedback and we’re planning to make some changes to the project before it launches.
First, we’ll be improving the quality of the data that we ask our volunteers to work on. We’ve identified a few common types of subjects which can make it more difficult for volunteers to find the lensing events we’re looking for. This includes subjects where there are periodic (repeating) patterns and subjects where some of the data is offset from the rest (e.g. where you might see two horizontal bands of points instead of a single curve). Now that we’ve identified these common patterns they should be easy for us to filter out, so that our volunteers can focus on finding the lensing events that we’re interested in.
A lot of the comments we got were about the classification feedback system. This is a new Zooniverse feature that we were trialling. The idea is to provide feedback to volunteers while they’re classifying, by mixing a few known subjects in with the unknown ones and letting people know if their classification was correct or not. Unfortunately a lot of people found this feedback rather frustrating, since at the moment it’s not possible to show the volunteer exactly where their mistake was. While it’s useful to let people know if they’re getting things right, without more specific feedback it’s difficult for people to actually learn from it. Because of that we’re going to disable the feedback system for now. We’ll revisit it later once the Zooniverse team has had more time to work on it.
Finally, many people found the instructions for the project a little difficult to follow. We’ll be expanding the field guide to include more examples of difficult cases that more closely match the majority of the subjects in the project. We’ll also be updating the tutorial with some additional examples and we’ll be adding a video to the tutorial to demonstrate how the classification interface works. We’re also going to add a separate tutorial workflow to let people learn the ropes without affecting the real classification data.
As you can see, we’ve got plenty to keep us busy for now! We’re hoping to have the project ready for launch soon, though, and we’re excited to start hunting for black holes with all of you!
The SuperWASP project is currently funded and operated by Warwick University and Keele University, and was originally set up by Queen’s University Belfast, the Universities of Keele, St. Andrews and Leicester, the Open University, the Isaac Newton Group, the Instituto de Astrofisica de Canarias, the South African Astronomical Observatory and by STFC.
The Zooniverse project on SuperWASP Variable Stars is led by Andrew Norton (The Open University) and builds on work he has done with his former postgraduate students Les Thomas, Stan Payne, Marcus Lohr, Paul Greer, and Heidi Thiemann, and current postgraduate student Adam McMaster.
The Zooniverse project on SuperWASP Variable Stars was developed with the help of the ASTERICS Horizon2020 project. ASTERICS is supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement n.653477
VeSPA was designed and developed by Adam McMaster as part of his postgraduate work. This work is funded by STFC, DISCnet, and the Open University Space SRA. Server infrastructure was funded by the Open University Space SRA.