PI - should be You, but Posted by Dr. Carol Christian, carolc[at]stsci.edu, www.stsci.edu/~carolc
Project duration: Usually Several Months
Abstract: This page is to alert researchers and students to the possibility of conducting research based peer reviewed work enabled through the simple training and activity of a cadre of citizen science volunteers. There are ample examples of such projects across all scientific disciplines. This is research aimed not outreach aimed. There now is funding from NASA.
Work to be done by students: Assemble the data, plan out the project overview and the training needed for the volunteers, set up of the website and training modules, create the other necessary software and interfaces. There is a toolkit from Zooniverse.
This is an example of a past Citizen Science Project with HST data on star clusters in galaxies. There have been quite a few citizen science projects with HST data, some conducted at JHU. There are other examples such as the citizen science project on M31 by Julianne Dalcanton, and Galaxy Mergers as well as Galaxy Zoo Hubble. If any faculty or postdoc has a research project that would lend itself to processing of data visually or with simple analysis by many people with some simple training, then that project is suitable for citizen science. It should be a project that has sufficient data that human classification or processing is too time-consuming to accomplish with one person or a small team but needs some "ground truth" verification of machine algorithms nonetheless.
The additional good news is that NASA Science Mission Directorate is providing funding and for JHU researchers who could take advantage of citizen science volunteers, this new program provides such funding. I emphasize this is for RESEARCH. This is not outreach money. It is expected that peer reviewed research results. If the volunteers learn something about astronomy, analysis and machine learning along the way, then so be it.
Any way, it is real MONEY and if researchers are interested at JHU they should apply. Again, should be a project that has sufficient data that human classification or processing is too time-consuming to accomplish with one person or a small team but needs some "ground truth" verification of machine algorithms nonetheless. Besides galaxies, one of the projects we did at ST (below) was to have volunteers classify star clusters as to age which was then correlated with photometry.
ROSES-20 Amendment 52: Release of Final text of Citizen Science Seed Funding Program
On or about September 11, 2020, this Amendment to the NASA Research Announcement "Research Opportunities in Space and Earth Sciences (ROSES) 2020" (NNH20ZDA001N) will be posted on the NASA research opportunity homepage at http://solicitation.nasaprs.com/ROSES2020 and will appear on SARA's ROSES blog at: https://science.nasa.gov/researchers/sara/grant-solicitations/roses-2020/.
Questions concerning Citizen Science Seed Funding Program may be directed to Marc Kuchner, who may be reached at marc.kuchner@nasa.gov.
StarDate:M83
Galaxies are made of stars — but where do these stars come from? Most stars form in star clusters rather than in isolation. Many star clusters then dissolve over time, their stars spreading out to form the galaxy as a whole.
This is the central theme of the citizen science project, Star Date: M83, that is, to better understand the life cycle of star clusters, from infancy to old age and from formation to destruction. To do this we need to estimate the ages of star clusters and then study how many clusters there are at each age. Cluster populations may vary depending upon the host galaxy, particularly how star clusters form along its spiral arms or other regions.
In Project Star Date M83, citizen scientists paired their discerning eyes with the Hubble telescope’s detailed images to identify the ages of the Southern Pinwheel Galaxy’s (M83) many star clusters. This info helps researchers learn how star clusters are born, evolve and eventually expand and perhaps dissolve in galaxies, spirals in particular.
