kuroshio-lab.com
Kuroshio-Lab is an ambitious, one-year development roadmap to build a suite of five high-impact, cloud-native tools for marine biology research and citizen science. The architecture utilizes Next.js, Django (Python), and AWS to deliver five distinct applications—from Species Trackers to Advanced Monitoring Platforms—all unified under a microservice-style subdomain architecture (projectX.kuroshio-lab.com) for scalability and independence.
Overview
Project: Kuroshio-Lab Marine Biology Tools Suite (5-Project Roadmap)
Overview & Goal: Kuroshio-Lab is a structured initiative to deliver five dedicated web applications over a one-year period, each addressing a critical need in marine data collection, visualization, and analysis. The project demonstrates full-stack proficiency across modern cloud environments, data pipelines, and scalable application architecture.
Technical Architecture & Scalability:
- Decoupled Stack: Each tool utilizes a high-performance stack, primarily Next.js for the frontend and Django (Python) for the robust backend APIs and data processing.
- Cloud Infrastructure (AWS): The entire suite is designed for cloud-native deployment on Amazon Web Services (AWS), leveraging Route 53 for subdomain routing (
project1.kuroshio-lab.com, etc.) and services like EC2, S3, Lambda, and ECS to ensure resilience, scalability, and cost-efficiency. - Data Integration: A core feature across the roadmap is the integration with and ingestion from major external marine data APIs (e.g., NOAA, GBIF, Copernicus).
Technologies
Development Roadmap
Tracking progress across the 1-year development journey
1. Kuroshio-Lab Architecture & Identity Rollout
Q4 2025 – Q1 2026Establish a consistent brand identity and a shared, scalable AWS infrastructure to support all five applications. This includes setting up Route 53 subdomain routing (e.g., `tracker.kuroshio-lab.com`), defining base CI/CD templates, and creating a unified Next.js Design System for the frontends.
2. Marine Species Observation Tracker
Q4 2025 – Q1 2026Build core CRUD functionality for logging species sightings on an interactive map, including photo storage (S3) and initial API integration (GBIF/OBIS).
3. Ocean Data Dashboard
Q2 2026Focus on data pipeline design and visualization. The system uses Celery/AWS Lambda for periodic, asynchronous ingestion of real-time ocean data (e.g., NOAA, Copernicus) into PostgreSQL. The Next.js frontend displays this information via dynamic, interactive charts (Recharts/Plotly). Deployment is Dockerized and managed via a CI/CD pipeline to AWS ECS/Elastic Beanstalk.
4. Coral Reef Health Index
Q3 2026 – Q4 2026Develop an application that integrates a small Python ML model (regression/classification) to predict coral bleaching risk. The process involves building an ETL pipeline to fetch and store satellite sea surface temperature data, deploying the model within the Django API, and visualizing the prediction scores via a dedicated Next.js dashboard.
5. Marine Life Encyclopedia with Recommendation Engine
Q4 2026 – Q1 2027Create a rich, educational CRUD application focused on marine species. Key features include API integration for external data enrichment (WoRMS) and advanced search capabilities, including fuzzy search. An optional goal is to prototype a recommendation engine based on taxonomic similarity. The final application will be hosted on AWS ECS via Docker.
6. Marine Monitoring Platform
Q1 2027 – Q2 2027The flagship project: a unified monitoring interface aggregating high-volume data from multiple sources (NOAA, MarineTraffic, Global Fishing Watch). The backend utilizes a scalable Django GraphQL API supported by a resilient ingestion pipeline (Celery/Lambda). The platform is a production-level deployment on AWS ECS with comprehensive CloudWatch monitoring and complex map-layer visualization.