Climate controlling the formation of Zn-(Pb) supergene nonsulphide ores

enable a computer system and effectively allow them to ‘understand’ the data they process (Wojcik et al. 2016). This makes them potentially ideal to be used in the mineral exploration sector, where prospectivity studies are typically completed following labour intensive and time-consuming desktop studies. To address the dual challenge of exploring for increasingly hard to locate mineral deposits and more effectively using available geodata, IGS Xplore has been developed a new and innovative mineral prospectivity system which uses semantic technology. It is a unique knowledge-based software application that examines geodata-sets using a set of well-established, non-statistical, empirically based geological rules governing 50 known mineralisation models worldwide, ensuring that generated mineral prospectivity areas are not theoretical constructs but are based on actual geological conditions. The semantic technology used by IGS Xplore uses inference processes to automatically enrich geodata with geological meaning, discover new relationships between geodata and generate more comprehensive, descriptive data models. Furthermore, storing complex and varied datasets requires a level of interoperability and extensibility that only semantic technologies can offer. IGS Xplore also allows full traceability of prospectivity process and outcomes compared to statistical and neural analyses. We have recently released a series of base metal prospectivity maps for the Ngamiland District of Botswana using geodata available on the recently-launched Botswana Geoscience Portal, hosted by Geosoft (http:// www.earthexplorer.com/2016/New_base_metal_ prospectivity_maps_for_Botswana.asp) (Figure 1). The new prospectivity maps connect and interpret the datasets available on the Portal to bring out the potential of the data and add value, giving industry an indication of the Greenfield opportunities in underexplored or covered terranes. Using semantic technology in mineral exploration will enable a greater understanding of favourable locations for mineral deposits using existing geodata sources to maximise the value of acquiring this data.