Mnova Gears – MPublish (Starting Guide)

Importance of the topic

Efficient and standardized preparation of supporting information is critical for ensuring research integrity, reproducibility, and compliance with journal requirements. Manual assembly of primary data and metadata can be time-consuming and error-prone; Mpublish automates this process to facilitate data sharing and publication.

Objectives and overview of the guide

This guide demonstrates how to use Mpublish, a Mnova Gears plugin, to generate publication-ready supporting information from NMR datasets. It outlines each step of the workflow from data selection through to formatted report creation.

Methodology and workflow

• Data input: import raw and processed NMR files from disk or database.
• Experiment detection: set manual path masks or enable automatic detection with advanced filtering and inspection tools.
• Plugin activation: add Mpublish to the list of Mnova Gears plugins and open its settings dialog.
• Template selection: choose one of the built-in journal formats (e.g., Organic Letters or ACS) or request custom templates.
• Metadata entry: specify publication title, authors, affiliations, and additional notes or abstract.
• Output configuration: define disk or database output, select desired formats (ODT, Mnova, PDF), and set target directory or server connection.
• Execution: launch the analysis to generate a timestamped output folder containing all results and logs.

Instrumentation

Mpublish runs within the Mnova Gears environment, processing NMR raw data files and Mnova (.mnova) processed spectra. It leverages the Mnova platform for spectral analysis and annotation.

Main results and discussion

The workflow produces:

• A fully formatted supporting information document (ODT) with templated experimental details.
• A reorganized archive of raw data files matched to report titles.
• Optional Mnova and PDF versions of the report.
• Execution logs and configuration snapshots for troubleshooting and audit trails.

Benefits and practical applications

• Significant reduction in manual effort and risk of errors.
• Consistent output that meets journal formatting standards.
• Improved reproducibility and data traceability.
• Support for centralized data archiving and retrieval via database integration.

Future trends and potential applications

• Extension to other spectroscopic techniques beyond NMR (e.g., MS, IR).
• Development of additional journal and custom reporting templates.
• Enhanced cloud and collaborative database connectivity for large-scale data management.
• Integration with FAIR data initiatives and electronic lab notebook systems.

Conclusion

Mpublish streamlines the generation of supporting information for NMR-based research, boosting efficiency, standardization, and reproducibility. Its flexible architecture and template-driven approach position it as a valuable tool for contemporary analytical chemistry workflows.