This position paper introduces the utilityof the conceptual spaces theory to conceptualisethe acquired knowledge in data-totextsystems. A use case of the proposedmethod is presented for text generationsystems dealing with sensor data. Modellinginformation in a conceptual spaceexploits a spatial representation of domainknowledge in order to perceive unexpectedobservations. This ongoing work aimsto apply conceptual spaces in NLG forgrounding numeric information into thesymbolic representation and confrontingthe important step of acquiring adequateknowledge in data-to-text systems.