Mnova DB Server (User Manual)

Importance of Topic

Centralized data management solutions are essential in analytical chemistry to support collaborative research, maintain data integrity and meet regulatory requirements. A shared server for spectra, molecular structures and experimental annotations streamlines workflows and reduces redundancy.

Objective and Overview of the Manual

This manual presents MnServer 2.0, a scalable database server developed by MestreLab Research for storing and sharing Mnova objects such as NMR, MS and other analytical data. It guides users through installation, configuration, user management and audit trail setup for three editions: MyData, MnDB Group and MnDB Enterprise.

Methods and Used Instrumentation

MnServer relies on a Java runtime environment and connects to a backend database. Key components include:

• Operating systems: Windows 7 or higher, macOS 10.13+, Linux distributions supporting Java
• Java runtime: version 1.8 minimum; 1.11 recommended
• Database backends: SQLite for MyData and MnDB Group; Oracle, MySQL or PostgreSQL for MnDB Enterprise
• Hardware: multi-core processor, 1 GB RAM or more, network connectivity for client-server communication
• MnServerAdmin and TestClient utilities for configuration and validation

Key Outcomes and Discussion

The manual details:

• Quick start procedures for installing server and client components
• System requirements to ensure reliable performance under varying workloads
• Step-by-step installation on Windows, macOS and Linux, including headless modes
• License activation workflow using host ID for MnDB Group and Enterprise
• Database connection setup via MnServerAdmin, with test and save functions
• User and permission management in standalone and Active Directory modes
• Service management: starting, stopping and installing MnServer as OS service
• Audit trail configuration capturing SQL operations, user IDs and timestamps for compliance

Benefits and Practical Applications

MnServer provides:

• Cross-platform data sharing among researchers on different operating systems
• Fine-grained user roles for secure access control and collaborative editing
• Flexible backend options to integrate with existing enterprise databases
• Audit trail capability for tracking changes and meeting quality assurance mandates
• Lightweight deployment using SQLite or full RDBMS support for large installations

Future Trends and Potential Applications

Emerging developments include integration with cloud infrastructure, automated data pipelines linking analytical instruments directly to the server, enhanced web-based portals and machine learning-driven metadata curation. Standardized APIs may further enable live data streaming and interoperability with electronic lab notebooks and LIMS platforms.

Conclusion

MnServer 2.0 delivers a comprehensive, platform-agnostic solution for centralizing analytical chemistry data. Its modular architecture, robust security options and audit capabilities facilitate collaboration, regulatory compliance and efficient data management across academic and industrial laboratories.