Symbolic objects were originally intended to bring both more structure in data and more intelligibility in final results to statistical data analysis. We present here a framework of similar motivation, i.e., combining a data analysis method, —the concept analysis (fca) — with a knowledge description language inspired by description logic (dl) formalism. The focus is hence on proper handling of relations between individuals in the construction of formal concepts. We illustrate the relational concept analysis (rca) framework which complements standard fca with a dedicated data format, a set of scaling operators, an iterative process for lattice construction, and translations to and from a dl language.