Collaborative Research: HCC: Medium: Intelligent support for non-experts to navigate large information spaces

Submitted by crowston on Wed, 2022-06-15 14:04

Apparently we never posted the news of our latest Gravity Spy NSF award, HCC 21-06865, Collaborative Research: HCC: Medium: Intelligent support for non-experts to navigate large information spaces, which was awarded in October 2021. This is a joint project with Kevin Crowston and Carsten Østerlund (Syracuse), Corey Jackson (Wisconsin), Aggelos Katsaggelos, Vassiliki Kalogera, Christopher Berry and Scott Coughlin (Northwestern), and Marissa Walker (Christopher Newport).

INSPIRE: Teaming Citizen Science with Machine Learning to Deepen LIGO's View of the Cosmos

Submitted by crowston on Mon, 2015-10-19 16:56

This project (INSPIRE 15-47880) has developed a citizen science system--Gravity Spy ()--to support the Advanced Laser Interferometer Gravitational wave Observatory (aLIGO), the most complicated experiment ever undertaken in gravitational physics. LIGO has opened up the window of gravitational wave observations on the Universe.

Previous grants

Submitted by crowston on Mon, 2015-10-19 16:55

Our research on citizen science has been funded by three earlier NSF awards. You can see the descriptions linked below.

Special issue on The Future of Artificial Intelligence and Citizen Science

Submitted by crowston on Mon, 2024-12-09 16:18

Our special collection on The Future of Artificial Intelligence and Citizen Science was just published in Citizen Science: Theory & Practice. Check it out !

 

 

Artificial Intelligence and the Future of Citizen Science

Fortson, L., Crowston, K., Kloetzer, L., & Ponti, M.. (2024). Artificial Intelligence and the Future of Citizen Science. Citizen Science: Theory And Practice, 9(1), 32. https://doi.org/10.5334/cstp.812

Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy

Folksonomies in crowdsourcing platforms: Three tensions associated with the development of shared language in distributed groups

Bullard, J., Crowston, K., Jackson, C. B., Smith, A. O., & Østerlund, C.. (2024). Folksonomies in crowdsourcing platforms: Three tensions associated with the development of shared language in distributed groups. In The European Conference on Computer-Supported Cooperative Work (ECSCW). https://doi.org/10.48340/ecscw2024_n06

Mutual learning in human-AI interaction

Østerlund, C., Crowston, K., Jackson, C. B., Takou-Ayaoh, M., Wu, Y., & Katsaggelos, A. K.. (2024). Mutual learning in human-AI interaction. In Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference. Presented at the Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference, Honolulu, HI.

Gravity Spy: Lessons Learned and a Path Forward

Zevin, M., Jackson, C. B., Doctor, Z., Wu, Y., Østerlund, C., L. Johnson, C., et al.. (2024). Gravity Spy: Lessons Learned and a Path Forward. European Physical Journal Plus, 139, Article 100. https://doi.org/10.1140/epjp/s13360-023-04795-4

Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications

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