CareConnect – Centralized Volunteer Management Platform

CareConnect is a volunteer management system built to support community-focused organizations like NAMI Yolo. It helps nonprofits recruit, onboard, train, and schedule volunteers with ease. The platform is built for accessibility, especially for organizations currently managing data across multiple spreadsheets and forms.

This submission includes:

• A dynamic web dashboard for real-time visual insights into volunteer trends.
• A reproducible Google Colab notebook for static data visualizations. (OpenData Hack)
• A publicly accessible dataset used to simulate real-world volunteer data.

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Why CareConnect?

Many mental health and nonprofit organizations rely on manual, spreadsheet-based workflows for managing volunteers. This makes it hard to:

• Track training completions and event history
• Match volunteers with relevant tasks
• Analyze community engagement patterns

CareConnect replaces this with an intuitive platform accessible to non-technical staff and optimized for social impact. It centralizes data and empowers admins to make informed decisions through both real-time dashboards and AI-driven insights (planned).

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Hackathon Tracks Alignment

This project was submitted to multiple tracks of HackDavis 2025, including:

• Best Hack for Social Good – Solving volunteer management for nonprofits like NAMI Yolo
• Open Data Hack – Uses a public dataset for static and dynamic visualizations
• NAMI Yolo Challenge – Specifically built around their current spreadsheet-based limitations
• Best Use of Auth0 – Role-based access and authentication
• Best Use of Cerebras API – Project is using Cerebras API
• Hackers' Choice Award

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Open Data Hack Track: Dataset & Visualizations

We did not have access to UC Davis-specific datasets, so we used a publicly available Kaggle dataset of NYC volunteer opportunities, which closely mirrors UC Davis volunteer activities.

UC Davis or similar institutions can easily adapt CareConnect for:

• Matching students with on-campus jobs or volunteering roles
• Visualizing department-wise participation
• Making data-driven decisions for outreach and equity

Static Visualizations

We provide a Python-based notebook for reproducible, high-quality charts submitted as part of the Open Data Hack track.

Includes:

• Heatmaps
• Category trends
• Borough distributions
• Volunteer request summaries

Static Visualizations (Google Colab)

These are quick, high-quality summary charts and heatmaps built using Python and matplotlib/seaborn. They help identify:

• Daily volunteer activity trends
• Event types distribution (ongoing vs one-time)
• Borough-wise event density
• Monthly growth across volunteer categories
• Summary statistics (events, volunteers, categories, etc.)

These are intended for Open Data Hack submission as reproducible and static visuals.

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How to Run Static Visuals in Google Colab

1. Go to Google Colab.
2. Upload the dataset file:
   nyc-service-volunteer-opportunities.csv
3. Upload the Python notebook or paste the script.
4. Run each cell one by one.
5. Download the generated .png files.

📁 Output files:

• summary_stats.png
• activity_heatmap.png
• category_trends.png
• borough_distribution.png
• event_types.png

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Dynamic Dashboard Web App

Built with React.js and Chart.js, this live dashboard allows:

• 🔎 Interactive filtering by Borough and Category
• 📅 Heatmap of activity like GitHub contribution graph
• 📊 Live bar and line charts updating with filters
• 🧠 Insight into trends for policy-makers or civic leaders

This version is ideal for embedding into platforms that track community engagement or helping organizations make data-driven volunteer planning decisions.

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Tech Stack

Component	Technology Used
Frontend	React.js, Chart.js, TailwindCSS
Backend/API	Node.js + Express (CSV served as API)
Static Charts	Python, Pandas, Matplotlib, Seaborn
Dataset Source	NYC Open Data on Kaggle

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Local Development Setup

1. Clone the repository

git clone https://github.com/shahchayan9/CareConnect.git
cd CareConnect

2. Install Dependencies

# Install server dependencies
cd server
npm install

# Install client dependencies
cd ../client
npm install

3. Environment Setup

# Create .env file in server directory
cp server/.env.example server/.env

# Update the following variables in .env:
AUTH0_DOMAIN=your-auth0-domain
AUTH0_AUDIENCE=your-auth0-audience

4. Start Development Servers

# Terminal 1 - Start backend server
cd server
npm start

# Terminal 2 - Start frontend development server
cd client
npm start

5. Access the Application

• Frontend: http://localhost:3000
• Backend API: http://localhost:5001

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Data Schema

The visualizations process the following key fields from the dataset:

Field	Description	Usage in Visualizations
category_desc	Event category description	Category filtering and trends
Borough	NYC borough location	Geographic distribution
created_date	Event creation date	Time-based analysis and heatmap
vol_requests	Number of volunteers requested	Demand analysis and statistics
recurrence_type	Event type (one-time/ongoing)	Event type distribution

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Usage Scenarios

• 📍 Identify under-served boroughs or neighborhoods
• 📅 Find seasonal spikes in volunteering (e.g., holidays)
• 🧑‍🏫 Determine student departments with highest participation (if adapted to UC Davis)
• 🤝 Guide nonprofits in launching more balanced opportunities

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Future Work

• Add map-based visualization using latitude/longitude
• Enable CSV upload for other datasets like UC Davis
• Enable volunteer recommendation and skill matching
• Add export functionality for reports and insights
• Implement user authentication and role-based access
• Add real-time data updates and notifications

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Submission

This project is submitted for:

• HackDavis 2025 – Open Data Hack (Social Good Track)
• By: Team CareConnect

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Acknowledgments

• NYC Open Data for providing the volunteer opportunities dataset
• HackDavis organizers for the opportunity
• Open source community for the amazing tools and libraries