Noema-Bot😄(1.0 version-October 2025)

Merging analysis, automation, and aesthetics in open science.

Noema-Bot, created by @TaliaChen, is a modular research assistant that analyzes data, generates dynamic reports, and transforms scientific results into simple, reproducible web pages. It integrates lightweight Python analysis pipelines with Quarkdown-based HTML rendering, creating an end-to-end framework for transparent, automated scientific reporting.

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Overview

Modern research often faces two common challenges:
1️⃣ Repetitive analysis workflows: running the same data cleaning, visualization, and reporting steps for every new dataset.
2️⃣ Inconsistent formatting and documentation: results are stored in different styles and formats, making reproducibility difficult.

HOWEVER! Noema-Bot is designed to address those problems.
It acts as a lightweight automation layer that connects data → analysis → visualization → publication, all within a single reproducible environment.

Instead of being just another script runner, Noema-Bot functions as a mini framework for open, aesthetic, and transparent research , helping users transform raw data into structured, publication-ready web reports with minimal effort.

Aims to

Noema-Bot is built to make automated, reproducible reporting accessible across different levels of research and development.

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Students and early-career researchers

• who want to structure their data workflows, analyze experimental results, and generate clean, professional reports — all through readable Python code.

Educators and mentors

• who need a simple, open-source teaching example to demonstrate reproducible analysis, visualization, or automation principles in class.

Citizen scientists and independent learners

• who conduct small-scale studies or personal experiments and want to share findings transparently using open tools.

Developers and data enthusiasts

• who are exploring how to integrate Python analysis scripts with GitHub Actions or automate analytical pipelines in public repositories.

Open-science and reproducibility advocates

• who value transparent, version-controlled research workflows and want a lightweight tool to support FAIR data practices.

Interdisciplinary creators

• combining design, storytelling, and science, seeking an aesthetic yet rigorous way to present research or data-driven projects.

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Features

• Automatic data analysis via Python scripts
  → Supports .csv, .xlsx, .json, and experimental data formats
• Customizable Quarkdown rendering
  → Converts analytical outputs into interactive HTML reports
• GitHub Actions integration
  → Trigger analyses automatically using /analyze commands or manual dispatch
• Modular structure
  → Easily extendable for new datasets or analysis types
• Beautiful report templates
  → Scientific yet minimal design for public sharing or presentation

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Usage

1️⃣ Run locally

git clone https://github.com/chentalia317-alt<your-username>/Noema-Bot.git
cd Noema-Bot
pip install -r requirements.txt
python scripts/analyze.py

2️⃣ Run via GitHub Actions

Comment in an Issue: /analyze + files name (example: /analyze file=panda.csv) or manually trigger the workflow from the Actions tab.
Your analysis results and report will be automatically uploaded to the repository.

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🧩 Note: The current version of Noema-Bot only supports histogram visualization.

However, the analysis pipeline is designed to be modular and extensible, allowing future integration of more advanced visualization methods (e.g., boxplots, density curves, and correlation heatmaps).
This structure makes it easy to expand Noema-Bot as a general-purpose scientific analysis assistant over time.

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Future Plans (WIP)

The current version of Noema-Bot focuses on basic visualization (only histogram) and automated report generation.
In upcoming updates, the project aims to expand its analytical and rendering capabilities to include:

• Advanced visualizations — integration of boxplots, density plots, correlation heatmaps, and time-series analysis...
• Modular analytics — support for plug-in modules that allow users to add their own data-processing scripts.
• Enhanced Quarkdown templates — improved report aesthetics, multi-section layouts, and interactive charts.
• Cross-dataset automation — enabling batch analysis for multiple files or longitudinal datasets.
• Web publishing — direct rendering of Quarkdown reports to GitHub Pages or other static-site platforms.

The long-term goal is to turn Noema-Bot into a flexible, open-source and effective assistant for transparent and aesthetic scientific reporting🤩.

🤝 Collaboration & Contribution

“Noema-Bot is not just a script — it’s a philosophy of open, reproducible, and aesthetic science.”

Noema-Bot is an evolving research assistant that connects data analysis, automation, and aesthetics.
It runs Python pipelines, analyzes datasets, and generates Quarkdown-based HTML reports — all designed to make open science more reproducible and beautiful.

I’m currently looking for collaborators or contributors who share this vision and would like to grow the project together.

Possible Collaboration Areas

• Data analysis & visualization — extending statistical modules, improving histogram/plot generation
• Automation & reproducibility — refining the GitHub Actions workflow, improving Quarkdown rendering
• Front-end / design — creating better dashboard layouts and visual templates
• Documentation & outreach — improving README guides, tutorials, or open-science communication

How to contact

• Fork this repository and open a pull request
• Or contact the maintainer: @chentalia317-alt
  (you can briefly describe your background or what you’d like to work on)