Data Diagram Design and Data Management for Visualisation and Analytics Fusion in the Mining Industry

Ruiyu Liang

Chaoran Huang

Chengguo ZhangEmail

Binghao Li

Serkan Saydam

Ismet Canbulat

The School of Minerals and Energy Resources Engineering, UNSW, Sydney, 2052, NSW,  Australia.


The adoption of advanced technologies in mining has resulted in large amounts of data. Yet, according to recent research, our ability to collect and store massive amounts of data far outstrips  our ability to manage and analyse the ever-increasing data, such as data exchange, information sharing, and multi-dimensional data fusion. In this paper, in order to facilitate the development of automated visualisation and multidimensional data-oriented analytics, we propose a visual analytics-oriented data diagram and data processing workflows. Firstly, we introduce visual model  data as a new modality in data management and analytics by standardising drawing data. Then, we extend the visual analytics into 3D spaces, for an enhanced interactive visualisation and various data access. This also enables to develop new schema for a comprehensive data-driven model for visualisation, which can be alternative to the conventional solid model and perform well in scalability and lifetime support. Furthermore, based on the unified data diagram and tile index concept, a multidimensional and multi-modality data management strategy is proposed for system scalability and lifetime support. Lastly, an effective data management targeting data fusion and 3D  visual analytics is implemented, providing constant data support in the trial of mining digitalisation.  Moreover, the outcome of this paper can give further technical support to digital twin system construction.