SCIENTRY – Scientific Entry System 🧬📊

SCIENTRY is a flexible, spreadsheet-inspired data management system designed to help researchers manage experimental data with structure, traceability, and collaboration in mind. Whether you're migrating from traditional spreadsheets or setting up a new project from scratch, SCIENTRY provides a user-friendly and robust environment to manage complex scientific datasets, protocols, and visualizations.

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🚀 Features

• Project-Based Organization
  Create project containers that hold one or more models (like spreadsheets).

• Flexible Data Models
  Each model:

  • Defines its own attributes (column-like fields) with types:
    input, number, select, or date.
  • Contains records (rows) with validation rules tied to attribute types.
  • Supports foreign key–like links between models.
  • Stores related protocol files (e.g., SOPs, PDFs, DOCs) and image files.

• Spreadsheet-Like Usability

  • Inline table editing of records
  • Validation at entry based on attribute types

• Powerful Role-Based Access Control

  • Admin: Full permissions
  • Project Manager: Full access within assigned projects
  • Data Manager: Create/update data for assigned models
  • Researcher: Read-only access

• Visual Reporting and Export

  • Download charts and reports per model
  • Visualize distributions and summaries directly in the app

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🔍 Use Cases

• Replace error-prone spreadsheets with structured and validated data entry
• Manage lab protocols and experimental files per dataset
• Coordinate multi-user collaboration with defined roles
• Maintain links between datasets via model references
• Generate quick visual insights and downloadable reports

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🧑‍🔬 Who Is It For?

• Research labs and institutions
• Bioinformatics and life science teams
• Environmental monitoring projects
• Any group needing structured scientific data management

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📦 Installation

You’ll be able to deploy SCIENTRY via docker compose

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📸 Screenshots

Coming soon...

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🛠 Tech Stack (Tentative)

• Backend: Python (Flask/FastAPI)
• Frontend: Vue 3 / Vite
• Database: PostgreSQL / MongoDB
• Charting: Chart.js / D3

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📄 License

MIT License — see LICENSE file for details.

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🤝 Contributing

Contributions, feature suggestions, and feedback are welcome!
Please open an issue or submit a pull request.

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📬 Contact

Developer: [Emilio Righi]
Email: [[email protected]]
Lab: Roderic Guigó Lab – CRG Barcelona

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