An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Potash mining is an important economic activity in the north-east of Spain. However, one of the main environmental issues produced for such type of mining is subsidence, which generates horizontal and vertical ground displacements. A Geographic Information System (GIS)-based model is proposed as a management system in a case study with two mines. This system is able to deal with subsidence data and its behavior over time. More than 1300 control points are included in the GIS, with data since 2007. These data processed by the GIS allowed determining the module, sense and direction of the displacements, the sinking velocity and the possible affectation of subsidence to infrastructures and buildings. Hence, the system created can be a useful tool to manage subsidence data, determine its evolution, predict future environmental and social impacts and control corrective measures.