Project Registry
The Project Registry tracks open source projects at GW
Students, faculty, and staff are encouraged to register publicly available projects to help us recognize and strengthen our GW open source community. To be eligible, a project must be shared under a standard public license (OSI-approved license for software, Open Data Commons or Creative Commons license for data or other works, or public-domain dedication). Projects should also align with the Open Source Definition, the Open Source AI Definition, or the Open Definition, as applicable. These definitions emphasize interoperability, open formats, and allowing the creation of derivative works. In addition, to be listed, a project should be a substantial original contribution by a GW student, faculty, or staff, and/or have originated from a GW-led collaboration. Please see the Project Submission Requirements for more details.
Projects
Individual and group projects maintained by GW community members.
deepBreaks
Project Lead: Mahdi Baghbanzadeh, Ali Rahnavard
Open-source software designed to analyze sequence data (such as DNA or amino acids) for genotype-phenotype associations using machine learning (ML). It addresses common challenges in sequence analysis, such as noise, nonlinear relationships, high data dimensionality, etc.
SimLogger
Project Lead: Joseph Kilgore
A method for logging simulation data in an easy and clean format. Never worry about losing data again, and always be prepared for when your PhD advisor asks "but what does this variable do across the simulation".
surveydown
Project Lead: John Paul Helveston, Pingfan Hu, Bogdan Bunea
The surveydown R package is a flexible, open-source platform for making surveys with R, Quarto, Shiny, and Supabase. With surveydown, you can design your survey using a Quarto document with markdown and R code, and easily convert it into a Shiny app. The survey data is stored in Supabase.
Python Camp
Project Lead: Dolsy Smith, Debbie Bezanson, Alex Boyd, Emily Blumenthal, Josh McDonald, Marcus Peerman, Max Turer
Python Camp is a non-credit, hands-on, intensive mini-course offered by GW Libraries & Academic Innovation (GW LAI) for the GW community. It introduces foundational programming practice using the Python language, with a focus on building skill through team-based activities & self-guided exercises.
The Gooseneck Barnacle Genome
Project Lead: Keith Crandall
The barnacles are a group of more than 2,000 species that have fascinated biologists, including Darwin, for centuries. Here we present the most comprehensive barnacle genome to date with open access data and analyses.
Practical Numerical Methods with Python
Project Lead: Lorena A. Barba
A full course teaching students how to connect the physics represented by a mathematical model to the characteristics of numerical methods, select appropriate solution methods, implement them correctly in computer programs, and interpret the numerical solutions obtained.
logitr
Project Lead: John Paul Helveston
Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations in R.
renderthis
Project Lead: John Paul Helveston
This package contains functions for rendering R Markdown and Quarto documents — primarily xaringan or revealjs slides — to different formats, including HTML, PDF, PNG, GIF, PPTX, and MP4, as well as a ‘social’ output, a png of the first slide re-sized for sharing on social media.
cbcTools
Project Lead: John Paul Helveston
Functions for designing surveys and conducting power analyses for choice-based conjoint survey experiments in R.
PyGIS
Project Lead: Michael Mann
This book will introduce you to the methods required for spatial programming. We focus on building your core programming techniques while helping you: leverage spatial data from OSM and the US Census, use satellite imagery, track land-use change, and track social distance during a pandemic, amongst others.
AeroPython
Project Lead: Lorena A. Barba
A set of lessons presenting a computational approach to a course in classical aerodynamics (potential flow), targeting advanced undergraduate students or master’s students in mechanical or aerospace engineering, with a fluid mechanics pre-requisite.
CFD Python: 12 steps to Navier-Stokes
Project Lead: Lorena A. Barba
The 12 steps to Navier-Stokes equations are a series of tutorials developed by Prof. Lorena Barba to teach students the fundamentals of computational fluid dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow.
GRAG
Project Lead: Arjun Bingly, Sanchit Vijay, Kunal Inglunkar, Erika Pham
GRAG is a Python package that lets users implement end-to-end RAG (Retrieval Augmented Generation) with ease. The package lets users seamlessly deploy a multitude of language models (LLMs), leveraging local deployment capabilities, quantization support, and effortless integration with vectorstores.
Screening Shakespeare
Project Lead: Alexa Alice Joubin
The openly-licensed learning modules in this Open Educational Resources (OER) introduce students to key concepts of film studies, such as mise-en-scène, cinematography, sound and music, and film theory within the context of film adaptations of Shakespeare’s plays.
Colonial Courses
Project Lead: Michael Rossetti
Colonial Courses makes it easy for students to know which courses are being offered in a given semester. Users choose a semester and input a list of departments, and the app provides an export of course registration information in CSV format.