1. A method for capturing expert knowledge and data comprising: receiving by a processing device expert knowledge and data entered via an editing device; storing the received expert knowledge and data into one or more tables of a database system, a first subset of the data being represented in the one or more tables as conclusion data, a second subset of the data being represented as observation data, and a third subset of the data being represented as relationship data; and generating by the processing device, based on the one or more tables, a probabilistic model that captures the entered expert knowledge and data, the probabilistic model including a structure of layers of nodes with at least one grouping layer disposed in-between a conclusion layer having a plurality of conclusion nodes designated as parent nodes and formed based on the stored conclusion data, and an evidence layer having a plurality of observation nodes designated as children nodes and formed based on the stored observation data, wherein a group node in the at least one grouping layer represents an aggregation of conclusions in two or more of the conclusion nodes in the conclusion layer, wherein the structure of layers of nodes includes directed arcs between the nodes based on the stored relationship data, with none of the directed arcs connecting two nodes in a same layer, and wherein at least one of the arcs is between the group node and at least one of the plurality of observation nodes, wherein, the generated probabilistic model is configured to be invoked by a reasoning engine for outputting probabilities of one or more conclusions or aggregation of the conclusions, in response to input observations, during a decision making process.