Knowledge-based query system for the critical minerals

Critical minerals are increasingly used in advanced, modern technologies. Exploration for these minerals require efficient mechanisms to search for the latest geological knowledge about the petrogenesis and spatial distribution of these essential resources. Although the current text-based deposit classification schemes help geoscientists to understand how and where these critical minerals form, they cannot easily be queried by software without extensive natural language processing and knowledge modeling. Ontologies can explicitly specify the knowledge scattered in the texts and tables of these schemes and the Critical Minerals Mapping Initiative (CMMI) database by way of logical structures whose results can automatically be processed and queried. They can also draw new knowledge by inference from the ones that are explicitly specified in them. These qualities make ontologies a perfect choice for digital knowledge storage, search, and extraction. The Critical Minerals Ontology (CMO) is described herein by reusing the logical class and property structures of the top-level Basic Formal Ontology (BFO) and mid-level Common Core Ontologies (CCO) and Relation Ontology (RO). The CMO formally models the knowledge about the critical mineral systems using the latest deposit classification scheme and the CMMI database schema. The ontology specifies the geochemical and geological processes that operate in various geotectonic environments of mineral systems to form the critical minerals in different deposit types. It models the properties of both the host minerals that contain the rare-earth elements and those that bear other types of elements. The CMO also represents uses of specific critical minerals in the manufacturing of industrial products, their alternate substitutes, and countries that produce, import, and export them. A query system, applying the Python programming language, accesses the knowledge modeled in the CMO and allows users through interactive web pages to query the ontology and extract different types of information from it. The ontology and the query system are useful for research in ore mineralogy and critical mineral prospecting. The information modeled by the ontology and served by the query system allows users to classify their ore specimen data into specific deposit types.