Framework components for data-centric dry laboratories in the minerals industry: A path to science-and-technology-led innovation

The world continues to experience a surge in data generation and digital transformation. Historic data is increasingly being replaced by modernized data, such as big data, which is regarded as data that exhibits the 5Vs: volume, variety, velocity, veracity and value. The capacity to optimally use and comprehend value from big data has become an indispensable aptitude for modern companies. In contrast to commercial and technology firms, usage, management and governance of data, including big data is a novel and evolving trend for mining and mineral industries. Although the mining industry can be unenthusiastic to change, embracing modernized data and big data is evolutionarily unavoidable, given many industry-wide challenges (i.e., fluctuation in commodity prices, geotechnical and harsh ground conditions, and ore grade), which corrode revenues and increase business risks, including the possibility of regulatory non-compliance. The minerals industry holds a genuine gold mine of data that were collected for scientific, engineering, operational and other purposes. Data and data-centric workspaces that are targeted towards innovation and experimentation, which if combined with in-discipline expertise are two harmonious ingredients that can provide many practical solutions for the mining and mineral industries. In this paper, the concept, the opportunity and the necessity for a move towards a technologyand innovation-based, data-centric 'dry laboratories' (common workspaces that facilitates data-centric experimentation and innovation) in the minerals industry are assessed. We contend that the dry laboratory environment maximizes the value of data for the minerals industry. Toward the establishment of dry laboratories, we propose several essential components of a framework that would enable the functionality of dry laboratories in the minerals industry, while concomitantly examining the components from both academia and industry perspectives.

Automated summary

The world is experiencing a surge in data generation and digital transformation. Modernized data, especially big data, is essential for modern companies. In contrast, the mining industry is relatively new in terms of using, managing, and governing data, including big data. Dry laboratories, which focus on data-centric experimentation and innovation, can maximize the value of data in the mining industry.