a b s t r a c t Sensor networks prompt a great deal of research interest within the computer and analytical sciences. To this regard, one of the most important issues is concerned with the interpretation of data that are collected by different sensors. Due to sensors non-reproducibility, this problem may also persist even when many replicas of the same sensors are considered. In this case additional calibrations may be required to use a common knowledge database. Noteworthy, the same problem arises in case of sensors replacement. In this paper we demonstrate that in case of optical chemical sensors drawing inspiration from the connectivity strategy of the olfactory bulb, this problem can find a straightforward solution when an image sensor is used to measure the optical properties of an extended sensing layer. If the sensing layer is formed by a number of spots of different indicators, it is demonstrated that a common data processing can be applied to any replica of the sensing layer even if the indicators are spotted with different geometries and in different quantities.