This readme file was generated on 2023-05-31 by Catherine Barber GENERAL INFORMATION Title of Dataset: Fondren Library Data Repository for Data Science Education and Experiential Learning Author Information Name: Anna Xiong Institution: Rice University Email: jax2@rice.edu Author Information Name: Su Chen Institution: Rice University Email: sc131@rice.edu Author Information Name: Catherine R. Barber ORCID: 0000000289039125 Institution: Rice University Email: cb88@rice.edu Author Information Name: Nik Sun Institution: Rice University Email: xs23@rice.edu Author Information Name: Alison Qiu Institution: Rice University Email: zq6@rice.edu Author Information Name: Tina Li Institution: Rice University Email: tcl3@rice.edu ABSTRACT This project piloted a process for creating a repository of interesting, real-world government datasets that are easy to access, beginner-friendly, and suitable for educational use, particularly in data science. The project resulted in three sub-projects, each of which uses one or more open government datasets to demonstrate the data science pipeline. * The first sub-project (1_mental_health_project) used the U.S. Census Bureau's Household Pulse survey to explore correlates of mental health during the COVID-19 pandemic. * The second sub-project (2_education_demographics_project) used the National Center for Education Statistics' National Household Education Survey and Common Core of Data along with the Texas Education Agency's graduation data to explore relationships among educational outcomes, student and family demographic variables, and county demographic diversity within the 12th grader population. * The third sub-project (3_economics_employment_project) used the U.S. Census Bureau's Current Population Survey and a wide range of financial data (COVID-related spending, Medicaid spending, GDP, and minimum wage) to explore the relationship beteen government fiscal relief measures and employment during recessions. The three sub-project folders include clean datasets, code for cleaning and analyzing the data, and interpretation of the results. These materials are suitable for a range of learners within data science, including both novices and those with advanced statistical skills. Date of project: 2022-09 to 2023-05 Geographic location of project: Rice University, Houston, TX, USA Information about funding sources that supported the collection of the data: Funding was provided by the Fondren Fellows Program at Fondren Library, Rice University. SHARING/ACCESS INFORMATION Licenses/restrictions placed on the data: No restrictions; all data were derived from open government sources and do not contain any identifying information. Links to publications that cite or use the data: Li & Barber (2023): https://hdl.handle.net/1911/114882 Qiu & Chen (2023): https://hdl.handle.net/1911/114894 Sun & Xiong (2023): https://hdl.handle.net/1911/114880 Was data derived from another source? If yes, list source(s): Bureau of Economic Analysis, U.S. Department of Commerce: https://www.bea.gov Centers for Medicare & Medicaid Services: https://www.cms.gov Federal Reserve Bank of St. Louis Economic Research: https://fred.stlouisfed.org National Center for Education Statistics: https://nces.ed.gov Texas Education Agency: https://tea.texas.gov U.S. Census Bureau: https://www.census.gov USA Spending: https://www.usaspending.gov FILE OVERVIEW File List: 1_mental_health_project.zip: Zip file containing a readme file (txt), datasets (csv), and Python code (ipynb) for sub-project 1. 2_education_demographics_project.zip: Zip file containing a readme file (txt), datasets (csv), and R code (pdf and rmd) for sub-project 2. 3_economics_employment_project.zip: Zip file containing a readme file (txt), datasets (csv), and Python code (ipynb) for sub-project 3. Information about each sub-project (file list, methodology, etc.) can be found within the readme file in the sub-project folder. Are there multiple versions of the project? No