Combining measured data about unknown objects into sets, where each set of data refers to the same object, is a challenging task. In particular, if data are fragmentary and only a small set of possible observables are given with each datum, this task is particularly difficult. With a layered perspective, and a systematic use of conflicts between data, we demonstrate a possibility to solve fragmented data fusion problems.