User Guide

Welcome to the SCIENTRY User Guide! This comprehensive guide will help you understand and effectively use the Scientific Entry System.

Overview

SCIENTRY is a flexible, spreadsheet-inspired data management system designed specifically for researchers. It helps you organize, validate, and manage your scientific data with structure and traceability.

Key Features

🧬 Project-Based Organization

• Create project containers to organize your research
• Manage multiple models within each project
• Maintain clear separation between different research initiatives

📊 Flexible Data Models

• Define custom attributes with various types (text, number, select, date)
• Set validation rules to ensure data quality
• Create relationships between different models

🔐 Role-Based Access Control

• Admin: Full system access and user management
• Project Manager: Full access within assigned projects
• Data Manager: Create and update data for assigned models
• Researcher: Read-only access to assigned data

📁 File Management

• Store protocol files (SOPs, PDFs, DOCs)
• Organize image files related to your data
• Maintain file associations with specific records

🔗 Data Linking

• Create foreign key-like relationships between models
• Maintain data integrity across your research
• Track dependencies and references

📈 Visual Reporting

• Generate charts and visualizations
• Export data in various formats
• Create custom reports for analysis

Getting Started

If you're new to SCIENTRY, start with our Getting Started Guide which will walk you through:

1. Setting up your first project
2. Creating your first data model
3. Adding initial records
4. Understanding the basic workflow

User Guide Sections

Projects

Learn how to create and manage projects, the top-level containers for your research data.

Models

Understand how to design and configure data models with custom attributes and validation rules.

Records

Master the process of adding, editing, and managing data records within your models.

Access Control

Learn about user roles, permissions, and how to manage access to your research data.

File Management

Discover how to organize and manage files associated with your research data.

Best Practices

Data Organization

• Use descriptive project and model names
• Plan your attribute structure before creating models
• Consider data relationships when designing models

Data Quality

• Set appropriate validation rules for your attributes
• Use required fields for critical data
• Regularly review and clean your data

Collaboration

• Assign appropriate roles to team members
• Use projects to separate different research initiatives
• Document your data models and processes

Security

• Regularly review user access permissions
• Archive projects when they're no longer active
• Back up your data regularly

Need Help?

• Documentation: This user guide covers all major features
• API Reference: For technical integration details
• Contact: Reach out to emilio.righi@crg.eu for support