As part of the Intelligent Informatics @ Bloustein webinar series, Gavin Rozzi led a comprehensive workshop introducing participants to GitHub as a powerful platform for academic analytics and data science workflows. This session was designed for researchers, students, and faculty members seeking to leverage modern development tools for their academic work.
Workshop Overview
The workshop provided hands-on instruction for participants to get started with GitHub from scratch, covering both fundamental concepts and advanced applications relevant to academic research and data science. The session emphasized practical skills that participants could immediately apply to their own projects and coursework.
Role and Context
This workshop was delivered in Rozzi’s capacity as Research Computing Specialist at the Rutgers Urban and Civic Informatics Lab (RUCI Lab), where he supported faculty and student research through advanced computational methods and tools. The presentation also drew on his experience teaching graduate courses in the Bloustein School’s Master of Public Informatics Program, bringing pedagogical expertise to the technical training.
Key Topics Covered
Getting Started with GitHub
Account Setup and Fundamentals
- Creating and configuring GitHub accounts
- Understanding repositories, commits, and version control concepts
- Navigating the GitHub interface and basic operations
- Best practices for repository organization and naming
Organizational Features
- Using GitHub organizations for research groups and teams
- Managing permissions and access controls
- Collaborative workflows and team coordination
- Setting up institutional repositories
GitHub for Academic Research
Code and Project Management
- Version control strategies for research projects
- Documenting code with README files and wikis
- Managing research data and analysis scripts
- Collaborating with co-authors and research teams
Reproducibility and Transparency
- Creating reproducible research workflows
- Sharing code and data with the research community
- Licensing considerations for academic work
- Archiving research code for long-term preservation
Data Science Workflows
Best Practices for Data Science Projects
- Structuring data science repositories
- Managing dependencies and computational environments
- Organizing datasets, scripts, and outputs
- Handling sensitive or restricted data appropriately
Integration with R and Python
- Using GitHub with RStudio and other IDEs
- Version controlling Jupyter notebooks and RMarkdown files
- Collaborative data analysis workflows
- Managing conflicts in collaborative coding
GitHub Actions for Automation
Automated Data Workflows
- Introduction to GitHub Actions and continuous integration
- Automating web scraping and data collection
- Scheduled data acquisition pipelines
- Building automated data processing workflows
Dynamic Visualizations with RMarkdown
- Creating automated reports with RMarkdown
- Rendering dynamic visualizations on schedule
- Updating dashboards and interactive graphics
- Integrating external data sources
Web Publishing with GitHub Pages
Static Website Hosting
- Introduction to GitHub Pages
- Publishing research websites and portfolios
- Hosting project documentation and reports
- Custom domains and site configuration
Academic Applications
- Creating personal academic websites
- Hosting course materials and syllabi
- Sharing research outputs and publications
- Building interactive data visualizations online
Practical Applications
The workshop emphasized real-world applications relevant to the Bloustein School community:
Research Applications
- Managing code for journal publications
- Sharing replication materials
- Collaborating on grant-funded research projects
- Documenting research methods and protocols
Teaching Applications
- Distributing course materials and assignments
- Collecting and reviewing student code submissions
- Teaching version control and collaboration skills
- Creating interactive learning resources
Professional Development
- Building a professional portfolio
- Showcasing technical skills to employers
- Participating in open-source communities
- Networking with other researchers and practitioners
Target Audience
The workshop was designed for:
- Graduate students conducting data-intensive research
- Faculty members leading research projects
- Research staff supporting computational work
- Anyone interested in modern research computing tools
No prior programming experience was required, making the workshop accessible to participants from diverse academic backgrounds within the Bloustein School’s planning and public policy programs.
Learning Outcomes
Participants gained practical skills to:
- Create and manage GitHub repositories for their research projects
- Implement version control workflows in their daily research activities
- Collaborate effectively with team members on shared code and data
- Automate data collection and processing using GitHub Actions
- Publish research outputs via GitHub Pages
- Apply best practices for reproducible and transparent research
Connection to RUCI Lab Mission
This workshop exemplified the RUCI Lab’s commitment to:
- Building technical capacity among students and researchers
- Promoting reproducible research practices
- Advancing data-driven decision-making in planning and public policy
- Fostering innovation through modern computational tools
By introducing these tools to the Bloustein community, the workshop supported the lab’s broader mission of applying urban and civic informatics to address real-world policy challenges.
Related Projects
The techniques taught in this workshop directly support several projects and initiatives:
- COVID-19 Visualization - Using GitHub Actions for automated data updates
- OPRAmachine - Open-source development and collaboration
- zipcodeR Package - Publishing R packages on GitHub
- Academic research workflows - Version control for research code and data
Impact on Teaching and Research
As an instructor in the Master of Public Informatics Program, Rozzi incorporated these GitHub-based workflows into his graduate courses, ensuring that students developed practical skills alongside theoretical knowledge. This approach prepared students for careers in data-driven public sector and nonprofit organizations where version control and collaborative coding are increasingly essential.
The workshop’s emphasis on automation and reproducibility aligned with growing expectations in academic research for transparent, replicable methods. By introducing these tools at the graduate level, the workshop helped establish a foundation for rigorous, modern research practices among future planning and public policy professionals.
Technical Depth and Accessibility
The workshop balanced technical depth with accessibility, introducing complex concepts through practical demonstrations and hands-on exercises. Participants worked through real examples relevant to planning and public policy research, making abstract version control concepts concrete and immediately applicable.
The progression from basic account setup through advanced automation ensured that participants at all skill levels found value in the session, whether they were complete beginners or had some prior exposure to version control concepts.
Long-Term Skills Development
Beyond the immediate technical skills, the workshop introduced participants to the broader ecosystem of open-source development and collaborative research. Participants learned not just how to use GitHub, but why these tools matter for:
- Scientific integrity and reproducibility
- Collaborative research and knowledge sharing
- Professional development and career advancement
- Participating in broader research communities
- Contributing to open data and open science movements
These concepts reinforced the Bloustein School’s emphasis on evidence-based policy and transparent, accountable governance.
Format and Delivery
As part of the Intelligent Informatics @ Bloustein series, the workshop was delivered as a webinar, making it accessible to participants regardless of their physical location. This format supported engagement from students, faculty, and practitioners across the Rutgers community and beyond.
The interactive format included:
- Live demonstrations of GitHub functionality
- Step-by-step tutorials participants could follow along with
- Q&A sessions addressing specific use cases
- Practical examples from academic research contexts
- Resources for continued learning and exploration
This workshop represented the RUCI Lab’s commitment to building technical capacity across the Bloustein School community and advancing data-driven approaches to planning and public policy research.