Log QM

Overview

Log QM is a specialised component within the SABLE® solution, designed to support geoscientists in collecting accurate, high-quality data—especially while operating in remote field environments where internet connectivity may be limited or unavailable.

At its core, Log QM provides an offline database environment that mirrors the data standards, structure, and validation rules of the live SABLE database. This means geoscientists can confidently capture data in the field knowing it will comply with the same integrity checks used in the central system, ensuring seamless integration and consistent data quality.

Note: While Log QM offers robust field data collection capabilities, SABLE also features a more comprehensive module called LogIT, which includes additional advanced logging and data management functionality.

Why Log QM Is Needed

Fieldwork environments are often characterised by harsh conditions, limited power, and unreliable or non-existent network connectivity. Log QM addresses these challenges by enabling real-time data entry and validation on rugged, field-ready devices.

  • Immediate Validation at the Point of Capture: As data is entered, Log QM applies predefined validation rules. Users receive instant alerts for out-of-range values, missing fields, or formatting issues, reducing the likelihood of errors that would otherwise go unnoticed until post-processing.
  • Offline Capability: Users can continue to log and validate data without needing to be connected to a network. This capability ensures uninterrupted workflow in areas with limited connectivity.
  • Data Consistency Across Environments: Log QM ensures that all data collected offline is aligned with the standards of the live database. This eliminates discrepancies and reduces the need for time-consuming manual data correction after fieldwork.
  • Reduced Reliance on Spreadsheets: Traditional spreadsheet-based data collection introduces risks such as manual errors, inconsistent formats, and version control issues. Log QM replaces this with a robust, automated system that ensures only validated, structured data is captured.

Current Industry Practices and Challenges

Despite advancements in digital solutions, the use of spreadsheets for geological logging and field data collection remains common across the industry. However, this approach presents several risks and limitations:

  • No enforced data validation, which results in inconsistencies and errors.
  • Lack of integration or automated syncing between multiple data sources.
  • Version control issues when several users attempt to edit the same file simultaneously.
  • Difficulty in maintaining standardised formats across teams and locations.
  • Increased risk of data loss, accidental deletion, or unauthorised modifications.
  • Delayed quality checks, leading to the propagation of inaccurate or incomplete data through the workflow.

These challenges make it clear that a more structured, digitally-enabled solution is essential for modern exploration and mining operations.

Log QM Value

Log QM delivers significant operational and data quality benefits:

Efficiency

  • Real-time validation reduces manual post-fieldwork corrections.
  • Streamlines field operations, allowing geoscientists to focus on capturing insights rather than fixing errors.
  • Faster access to usable data enables quicker decision-making.

Data Consistency and Integrity

  • Validations help ensure that all captured data is correct, complete, and standard-compliant.
  • The sync and merge process ensures only quality-assured data is written back to the live SABLE database.
  • Reduces the risk of conflicts, duplicates, or overwrites during data integration.
  • Ensures data integrity is maintained during migration or synchronisation between offline and live environments.

Centralised Data Management

  • Moves data collection away from fragmented Excel files to a unified platform.
  • Enables centralised storage, traceability, and access control.
  • Facilitates easier auditing, reporting, and analysis.

Simplified Workflows

  • Eliminates the need to manually manage multiple spreadsheet versions.
  • Minimises opportunities for human error through automated checks.
  • Supports audit trails and user accountability through controlled data entry environments.