1. A method for automatically generating a semantic diagnosis model from a list of data points, the method comprising: sensing, by using a network of sensors, a time series of temperatures of a room; receiving, by a computer system, the time series of temperatures from the network of sensors, to be used to create a semantic diagnosis model; automatically creating, by the computer system, the semantic diagnosis model based on the received time series of temperatures, the automatically created diagnosis model reflecting rules that determine one or more potential causes of one or more abnormalities associated with one or more conditions in the room, including creating a plurality of models in sequence including said semantic diagnosis model, including creating a semantic data point model comprising the time series of temperatures semantically annotated, creating variables representing physical conditions indicated by the semantically annotated temperatures, generating from the semantic data point model and the created variables a semantic variable model comprising a data representation of the created variables, and using the semantic variable model in the creating said diagnosis model; determining, by the computer system and based on the received time series of temperatures, that the room has an abnormal temperature; and determining, by the computer system using the diagnosis model and said rules, one or more potential causes of the abnormal temperature, including mapping one of the created variables to said abnormal temperature, said one of the created variables being positively correlated in the diagnosis model with said abnormal temperature.