Astro Data Lab demo at the Empowering Science in the Data-Rich Era of Astronomy Conference

What: Astro Data Lab demo/tutorial at the "Empowering Science in the Data-Rich Era of Astronomy" conference
When: April 24, 2026 from 9:30am - 10:00am
Where: University of Arizona, ENR2 building, room S225

Agenda:

• Introduce Data Lab and its capabilities
• Live-demo of the integrated Web Portal, with queries, and image search & cutout
• Spectroscopy with SPARCL (NB demo)
• Time-domain /RRLyrae (NB demo)
• Q & A

If you want to follow along, get your free account now: https://datalab.noirlab.edu/account/register/

Details about the "Empowering Science in the Data-Rich Era of Astronomy" conference

The astronomical community has entered an era of rapidly evolving datasets of unprecedented volume and complexity, requiring cutting edge analysis resources and tools including AI and machine learning. NOIRLab is positioning itself to better support the community in this era of data and software-driven growth. With this conference, we will provide a forum for collaborative discussion of science enabled by data from surveys such as Rubin/LSST and DESI, and observing facilities such as Gemini, WIYN, SOAR, and CTIO, as well as joint studies with other surveys and facilities. The discussion at this meeting will inform the planning process for evolving the data, software and service products across NOIRLab.

Scientists are invited to present scientific cases that have been (or will be) enabled by rich data sets and cutting-edge analyses in fields including transient and variable discovery and characterization, galactic structure, cosmology, extragalactic science, the Local Universe, and the Solar System. We also welcome contributions on how to further advance scientific discoveries using AI and machine learning, advanced computing resources, software and service development, data archives and science platforms. We encourage discussions that touch on (but are not limited to) the following aspects:

• Coordination and joint scientific studies between different surveys and observing facilities.
• Opportunities and challenges as astronomers acquire large statistical samples of astronomical objects that were previously rare.
• AI-driven scientific discoveries and their infrastructure needs.