A powerful academic research mapping tool that clusters and visualizes scientific papers using state-of-the-art language models and unsupervised learning. ReMa provides an interactive interface to explore research topics spatially, identify key clusters, and access relevant literature.

[Watch the Demo Video](./FoPra submission/ReMa UI Demo Video.MOV)

• Features
• Tech Stack
• Installation & Setup
• Usage Guide
• Database Initialization
• Frontend Interface
• Troubleshooting
• Contributors
• License

• Download academic paper metadata from Semantic Scholar API
• Semantic clustering using SBERT → UMAP → HDBSCAN → BERTopic
• PostgreSQL database with pgvector support
• Flask backend API for frontend consumption
• Interactive frontend using deck.gl and Vue.js
• Topic labeling with LLM integration
• Supports scalable, containerized deployment via Docker

• Backend: Python, Flask, PostgreSQL, pgvector
• ML Pipeline: SBERT, UMAP, HDBSCAN, BERTopic
• Frontend: Vue.js, deck.gl
• DevOps: Docker, pgAdmin
• Database Visualization: pgAdmin 4

Follow these OS-agnostic steps (Mac/Windows) to set up the local environment.

• Download: pgAdmin.org/download
• Install and launch pgAdmin
• Create a master password

• Download: Docker Get Started
• Install and enable Docker (Hyper-V and WSL2 required on Windows)
• Verify:

  docker --version
  

docker pull ankane/pgvector

docker run -d --name pgvector-container \
  -e POSTGRES_USER=postgres \
  -e POSTGRES_PASSWORD=admin \
  -e POSTGRES_DB=RM_RUN \
  -p 5433:5432 ankane/pgvector

Confirm container is running:

docker ps

Connect to DB using pgAdmin:

• Host: localhost
• Port: 5433
• Username: postgres
• Password: admin

git clone https://github.com/Vinayak-biju/ResearchMap.git
cd ResearchMap
bash bootstrap.sh

This will set up a Python virtual environment and install all dependencies from requirements.txt.

1. Open pgAdmin
2. Connect to database RM_RUN
3. Execute the following SQL commands in order:

CREATE EXTENSION vector;
\i SQL/00_CREATE_PAPER.sql
\i SQL/01_CREATE_CLUSTER.sql
\i SQL/02_UPDATE_CLUSTER_CENTROIDS.sql
\i SQL/03_CLUSTER_SUMMARY.sql
\i SQL/04_SYSTEM_STATS.sql

python utils/DataDownload.py
python utils/main.py
python utils/app.py
python utils/chart.py

Script Descriptions:

• DataDownload.py: Pulls papers from Semantic Scholar and inserts into PAPER
• main.py: Runs the full clustering + topic modeling pipeline
• app.py: Launches the Flask API server (keep it running!)
• chart.py: Generates Publication Trend chart (for UI)

cd front_end
npm install
npm run serve

Access the app at: http://localhost:8080

Make sure app.py (Flask backend) is running in parallel.

• Docker not starting: Ensure virtualization is enabled (BIOS/UEFI)
• pgAdmin can't connect: Double-check port 5433, username/password
• Flask API errors: Check if pgvector-container is running and DB setup is complete
• Frontend not loading: Ensure npm packages are installed and server is started

• Vinaya Mukundan – 3810316
• Rohan Jojy Cherian – 3869174
• Vinayak Biju – 3844735

Copyright 2025 Marburg University

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
IN THE SOFTWARE.