🎓 Faculty Research Management System (FRMS)

A full-stack web application for managing faculty research profiles, publications, projects, and patents — built with Flask, MongoDB, and vanilla HTML/CSS/JS.

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📁 Project Structure

faculty-research-system/
├── backend/
│   ├── app.py              # Flask app — all API routes
│   ├── seed_data.py        # Seed MongoDB with sample data
│   └── requirements.txt    # Python dependencies
├── frontend/
│   ├── static/
│   │   ├── css/style.css   # All styling
│   │   └── js/app.js       # Frontend logic (Fetch API)
│   └── templates/
│       └── index.html      # Single Page Application shell
├── .env.example            # Environment variable template
├── .gitignore
└── README.md

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⚙️ Tech Stack

Layer	Technology
Backend	Python 3.10+, Flask
Database	MongoDB (NoSQL)
Frontend	HTML5, CSS3, JS (ES6+)
Charts	Chart.js
DB Driver	pymongo

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Setup & Installation

Prerequisites

• Python 3.10 or newer
• MongoDB Community Server (local) or MongoDB Atlas (cloud)
• pip
• Git

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Step 1 — Clone the Repository

git clone https://github.com/YOUR_USERNAME/faculty-research-system.git
cd faculty-research-system

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Step 2 — Set Up a Virtual Environment

# Create virtualenv
python -m venv venv

# Activate it
# Windows:
venv\Scripts\activate

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Step 3 — Install Python Dependencies

pip install -r backend/requirements.txt

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Step 4 — Configure Environment Variables

# Copy the example file
cp .env.example .env

Edit .env:

MONGO_URI=mongodb://localhost:27017/     
# OR for Atlas:
# MONGO_URI=mongodb+srv://<user>:<pass>@cluster.mongodb.net/
SECRET_KEY=your_random_secret_key_here

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Step 5 — Start MongoDB

Local MongoDB:

# Windows — start from Services or:
net start MongoDB

MongoDB Atlas:
Update MONGO_URI in your .env with your Atlas connection string.

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Step 6 — Seed Sample Data (Optional but Recommended)

cd backend
python seed_data.py

This inserts 4 sample faculty members and creates the default admin account.

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Step 7 — Run the Application

cd backend
python app.py

Open your browser and go to: http://localhost:5000

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Default Login

Username	Password
admin	admin123

⚠️ Change the password in production by updating the admins collection in MongoDB.

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API Reference

Authentication

Method	Endpoint	Description
POST	/api/login	Admin login
POST	/api/logout	Logout
GET	/api/auth/status	Check session

Faculty

Method	Endpoint	Description
GET	/api/faculty	List all faculty
GET	/api/faculty/<faculty_id>	Get faculty profile
POST	/api/addFaculty	Add new faculty
PUT	/api/updateFaculty/<faculty_id>	Update faculty
DELETE	/api/deleteFaculty/<faculty_id>	Delete faculty

Publications

Method	Endpoint	Description
POST	/api/addPublication/<faculty_id>	Add publication
PUT	/api/updatePublication/<faculty_id>/<pub_id>	Update publication
DELETE	/api/deletePublication/<faculty_id>/<pub_id>	Delete publication

Projects & Patents

Method	Endpoint	Description
POST	/api/addProject/<faculty_id>	Add project
DELETE	/api/deleteProject/<faculty_id>/<proj_id>	Delete project
POST	/api/addPatent/<faculty_id>	Add patent
DELETE	/api/deletePatent/<faculty_id>/<patent_id>	Delete patent

Search

Method	Endpoint	Query Params
GET	/api/searchFaculty	name, department, interest, pub_year, project_status, funding_agency

Dashboard

Method	Endpoint	Description
GET	/api/dashboard	Stats + analytics

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MongoDB Atlas Setup (Cloud)

1. Go to https://cloud.mongodb.com and create a free account
2. Create a new Cluster (free M0 tier works fine)
3. Under Database Access, create a user with read/write permissions
4. Under Network Access, add your IP (or 0.0.0.0/0 for development)
5. Click Connect → Drivers and copy the connection string
6. Paste it into your .env file as MONGO_URI

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Key MongoDB Queries Used

# Find faculty by department
collection.find({"department": "CSE"})

# Find by research interest
collection.find({"research_interests": {"$regex": "AI", "$options": "i"}})

# Top cited faculty (aggregation pipeline)
collection.aggregate([
    {"$project": {"name": 1, "total_citations": {"$sum": "$publications.citation_count"}}},
    {"$sort": {"total_citations": -1}},
    {"$limit": 5}
])

# Add embedded document
collection.update_one({"faculty_id": "FAC101"}, {"$push": {"publications": {...}}})

# Remove embedded document
collection.update_one({"faculty_id": "FAC101"}, {"$pull": {"publications": {"pub_id": "p1"}}})

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Features Implemented

• Admin login / session management
• Dashboard with live stats & charts
• Add / Edit / Delete faculty
• Add / Delete publications, projects, patents
• Faculty profile page with embedded records
• Multi-field search & filter
• Top-cited faculty analytics
• Funding agency analysis
• Department distribution chart
• Data validation & error handling
• MongoDB indexing (faculty_id, department, research_interests)
• Responsive design

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Author

Built as a NoSQL database project using Flask + MongoDB.