Abstract
Abstract
Mining projects generate heterogeneous data across files, platforms, and repositories, reducing interoperability and reuse. This paper proposes a local service oriented, edge enabled data management framework for mining. It addresses database selection, data standards, unified data structure, automated processing and cleaning, and local deployment under unstable connectivity, low latency demands, and data sensitivity constraints. The framework combines hybrid storage with a mining data standardisation profile covering reference settings, semantics, geometry, temporal state, provenance, and service payloads. A unified schema and automated workflow support harmonisation, validation, and incremental updates. A prototype built with FastAPI, MongoDB, Celery, Redis, ezdxf, and Unity demonstrates feasibility.