A Scalable Geo-Spatial Data Pipeline for Mining Ecosystems

The mining and exploration industry depends on large volumes of complex spatial and non-spatial data. However, many organizations still use fragmented systems, manual workflows, and isolated databases, causing data inconsistency, operational delays, and weak decision-making. This study presents a scalable Geographic Information System data pipeline designed to manage the full lifecycle of exploration and mining data, from field collection to enterprise visualization and decision support.

The proposed framework integrates multiple data sources, including geological mapping, drilling records, geochemical assays, remote sensing imagery, field observations, and operational datasets, into a unified enterprise GIS environment. The architecture includes data acquisition, ingestion and ETL, centralized storage, processing, analysis, and visualization. This modular structure improves interoperability, scalability, and data flow across exploration and mining workflows.

The system uses industry-standard platforms such as ArcGIS Pro, ArcGIS Online/Enterprise, MX Deposit, Microsoft Power Apps, and SharePoint. MX Deposit supports structured exploration data capture, while enterprise geodatabases provide centralized storage and management of spatial datasets. Power Apps enables customized data entry, validation, and workflow automation, while SharePoint supports secure document management and collaboration.

A key element of this framework is data governance, including metadata management, version control, role-based access, data validation, and quality assurance. These controls improve data reliability, traceability, and compliance with industry standards, which are essential for mining operations.

The framework was implemented in a real-world exploration environment and demonstrated measurable improvements in data management and operational efficiency. Results showed a 30–50% reduction in data processing time, improved data accuracy, real-time visibility of exploration activities, and stronger collaboration among multidisciplinary teams. The pipeline also supports integration with ERP systems, dashboards, advanced analytics, and future digital twin environments.

Overall, this research highlights the value of an integrated GIS data pipeline for modern mining operations and provides a scalable solution for transforming raw exploration data into actionable intelligence.