SOURCE-LINKED INTELLIGENCE

Exploration Information System

CORDIS · observation · Publication date unknown

oject consortium has also a vast international collaboration network, e.g. 50% of the Advisory Board members have been invited from outside EU. EIS will develop new data analysis methods by applying artificial intelligence, machine learning, deep learning into mineral prospectivity mapping together with new geomodels and mineral systems modelling. Methods developed reduce the current high exploration costs and improve the accuracy of the targeting of the early phase exploration. This makes mineral exploration responsible in terms of energy efficiency or minimizing footprint of mineral exploration on nature as the aim is to make most out of the already existing exploration data. Project will apply UNFC code to harmonize the diverse population of mineral deposits and occurrences which will be used as training sites and validation data sets in prospectivity mapping for critical raw materials within EU. In addition, tools will be tested for secondary raw materials prospectivity. Project will also raise awareness of general public on the importance of critical raw materials to the EU's e

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recordType

award

status

SIGNED

region

EU

value

7497032

unit

EUR