ExoCore is a curriculum of open science for the field of exoplanets developed as part of NASA's Open Science initiative. It complements Open Science 101 to provide a transparent and comprehensive curriculum covering the key tools, methods, and practices in the exoplanet research field through the use of interactive Jupyter notebooks. In a rapidly expanding field, ExoCore's primary goal is to give aspiring and current researchers exposure to state-of-the-art workflows to expedite their ability to contribute to the field. As a component of ScienceCore, ExoCore fulfills this goal in several ways: participants can actively practice these workflows, providing important 'hands-on' engagement; the lessons are filled with descriptive visuals, providing enriching context to potentially abstract and technical processes; the lessons are supplemented with hyperlinks that provide additional resources outside the scope of the lessons or provide alternative approaches to the methods and tools being taught.
ExoCore aims for the audience to be able to
- efficiently locate resources across exoplanet research,
- get inspired by examples on reproducible research workflows (e.g., transit modeling, spectroscopy reduction),
- jump-start in identifying interesting research problems and tackling them in the absence of local mentorship.
ExoCore is aimed toward advanced undergraduates and beginning graduate students.
Please refer to this presentation and worksheet of a workshop our team organized during AAS 245 in National Harbor, Maryland, on January 13, 2025, sponsored by a AAS Education & Professional Development (AAS-EPD) grant.
ExoCore is divided into seven modules that categorize lessons based on a particular aspect of exoplanet research. They include:
- Catalogs
- Data Repositories
- Data Structures
- Data Analysis and Modeling Software
- Utility Software
- Citizen Science
- Exoplanet Resources and Collaborations
Further information on module content and specific lessons can be found in the main ExoCore Jupyter notebook.
To efficiently curate which modules and lessons are best suited for an individual user, we have developed a pre-survey to assess both desired learning outcomes and preliminary proficiency in relevant topics. The output of the pre-survey will give a custom cirriculum which orders and outlines how to navigate the content of ExoCore. This will minimize content that is already familiar or not relevant for a given use case while still being comprehensive. This pre-survey is divided into two parts:
- Learning Outcomes and Familiarity Survey
- Pre-Curricular Assessment
The initial survey is used to gauge interest in particular topics or workflows, as well as prior experience in related software and topics. The assessment that follows will be generated based on the responses from the initial survey, and will gauge prior proficiency in relevant topics and softwares. The responses are then used to suggest a custom curriculum, as well as to measure the outcomes of ExoCore.
A post-curricular survey will be administered concluding ExoCore which will assess the efficacy of the lessons and modules completed. Additionally, it will solicit feedback on how ExoCore is administered, and any areas that were effective or could be improved.
You can explore ExoCore using Binder. Clicking the button below will generate a Docker image of ExoCore on BinderHub. The initialization process will take about two minutes.
We are always looking to expand ExoCore's curriculum, particularly from developers and current researchers. Please reach out via email at [email protected] if you are interested in contributing to the ExoCore curriculum.
ExoCore is developed by AstroMusers in the Department of Physics at Washington University in St. Louis. Nathan Whitsett and Bryce Wedig are the main developers. The other contributors to ExoCore include Ekrem Esmer, Aavik Wadivkar, Gabriella Jager, and Sophia Acker. Tansu Daylan is the principal investigator.
You can cite ExoCore and its contributors using the "Cite this repository" drop-down in the "About" section of ExoCore's GitHub page.
We acknowledge support from NASA through the grant 80NSSC23K0865 and by the McDonnell Center for the Space Sciences (MCSS) at Washington University in St. Louis.