Dr. Laura Trouille (VP of Citizen Science; Zooniverse, Adler, Northwestern) “LSST and The Crowd”. Project Builder Platform (PBP) makes Citizen Science projects like WordPress. There will be an automated way to send LSST images to the PBP. There’s now a communication channel between the APIs. Can be auto-updated with filters. Images should work. Metadata should work, but might need some work. Not hard to translate into multiple languages with “Translations Interface” and can invite volunteers to do it too. Can also organize multiple projects into a single organization. Quite impressive!
Combining human and machine classification, Supernova Hunters (Wright et al. 2018) shows that the combination are better than either. Now Galaxy Zoo has an updated workflow where a Machine Learning is used to prioritize which objects need to be classified by humans in an interactive automated way. Right now its a project by project basis, but may be a more developed version of the human-machine infrastructure may be available later.
PBP can be investigated at zooniverse.org/lab . There are and will be a variety of supporting infrastructure and help. Even when machine learning works well after a short human classification period, there is some desire to continue having humans interact with the data in order to find rare or unusual outcomes, even when the machine thinks it has correctly classified.
Next up, Mark SubbaRao and Aaron Geller talking about “Some cool Viz tools” as related to Visualization in the LSST era. Worldwide Telescope with new python interface (pyWWT). Can do a lot of things within a Jupyter notebook.
Aaron talking about Glue. Glue is a standalone, but also interfaces with a python shell. Allows for interactive multi-plot data selection. Concern about when there are many (>10^5 points). Zooming,
These can all interact with the Zooniverse system. Current focus on scatter-plot like diagrams.