Data Driven Amateur Astronomy

~ newton

Houston Astronomical Society December 5th, 2025

Modern astronomy research has become data-driven. Using data science techniques alongside computation allows us to interrogate data to understand astrophysical phenomena. The explosion of data sets has opened up new ways for enterprising amateur astronomers to contribute to modern astronomical research. Data can come from large-scale surveys, space-based observatories, individual scientists, or students. You can learn to select, reduce, visualize, and interpret authentic astronomical data while applying data science techniques to construct astronomy knowledge. Many free web-based tools leverage data science techniques. This talk explores how these activities bridge the gap between data science and astronomy, enabling amateurs to learn about both simultaneously.

The content of this talk can be cited as: Newland, J. (2025). Using Data Science in High School Astronomy. ASP 2024: Astronomy Across the Spectrum, 539, 147. http://arxiv.org/abs/2501.04856

The Google Colab (Jupyter Notebook) developed by Sara Kannan and me can be found here. Note that the actual catalog we created is not publicly available, so this notebook requires an existing catalog for SED creation.

If you are interested in data-driven astronomy learning, check out the page below from a talk given at the first-ever Data Science Education in K12 Conference. Even though the materials shared were designed for teaching high school astronomy, enterprising amateur astronomers can still pick up some cool tricks.

Integrating Data Science Pedagogy into Astronomy Courses

HOU’s Coding: Using CS for Science Teaching

~ newton

Integrating Computer Science into Science Teaching

When doing domain-specific programming in science, some CS pedagogy can be used to
scaffold concepts like conditionals, function writing, and looping. Using worked examples,
minimally working programs, sub-task labeling, and live coding can help a student bring
coding to bear on learning concepts in science. Room B107 1:15 – 2:15 pm CDT