Mining activity has been and is one of the most important and indispensable industries for the development of society. Given its role in the provision of raw materials, advancing the development of environmentally friendly mining practices is essential for meeting the globally established goals of sustainable development. In this regard, actions and incentives are being promoted by the European Union, such as the Mine.io project presented in this research. In response to the needs identified within the mining sector, this research seeks to explore the functional and non-functional requirements across several mining contexts. The objective is to establish effective patterns that positively influence the sector activities. This effort is envisioned as a critical foundation for developing a digital architecture that addresses sector limitations and fosters the integration of Industry 4.0 principles into the mining domain. The results provide a solid basis for understanding the needs of the different mining sectors analyzed, while also demonstrating the potential advancements achievable through the project’s technological developments. They enable a comprehensive evaluation of the current technological state in relation to the broader context of global legacy practices, establishing informed guidelines for effective sector responses based on digitalization and the application of sustainable tools.

Mining operations generate continuous sensor data across heterogeneous repositories with no unified access layer. Existing integration platforms either require centralizing data into new infrastructure or demand extensive pipeline reconfiguration when sources change. We present a metadata-driven execution model in which integration behavior is resolved at runtime from executable metadata rather than encoded in static workflows, preserving existing infrastructure while enabling unified access across heterogeneous repositories. An Asset Cataloging registry stores executable specifications, including connector identifiers, connection parameters, and routing rules, which select and invoke the appropriate connector at runtime without workflow coding or redeployment. Evaluation on large-scale real mining sensor datasets spanning heterogeneous formats (JSON, CSV, Parquet) and repositories (Kafka, MongoDB, external REST APIs) confirmed zero message loss and bit-exact binary reconstruction across all scenarios under at-least-once delivery with idempotent writes. Connector dispatch overhead fell below the 1 ms measurement resolution, confirming that integration latency is dominated by storage I/O rather than orchestration cost. Following evaluation, four pilot sites deployed the platform in production, spanning from active underground operations to post-mining waste management, under the EU Horizon Europe MINE.IO project, demonstrating viability at industrial scale.