Definition and construction of data models of big data entity for prospecting prediction of ore concentration area

This paper is the result of geological survey engineering and mineral exploration engineering.

Objective A set of methods and technologies for modeling big data entity data models is introduced, in order to predict prospects in mining areas. The connotation and extension of the big data entity data model is also defined.

Methods This paper is conducted on the fundamental principles of data modeling, the essential steps of database design, as well as the methods and technologies for entity data modeling in big data for predictive analysis in mining regions.

Results A universal scientific definition and modeling method technology system for the big data entity data model of prospecting prediction in mineral concentration areas is proposed.

Conclusions The technical specifications of the big data entity data model for prospecting prediction in mining areas were established, along with the development of the corresponding application support software system. This data model successfully integrated the theoretical methods and technical systems for prospecting prediction in mineral concentration areas, resulting in a scientific, systematic, hierarchical, standardized, and informatized approach to prospecting prediction work. These advancements have streamlined the complexity of prospecting predictions and minimized the uncertainty of prediction outcomes.