  Complexity remains one of the central challenges in science and technology.
Although several approaches at defining and/or quantifying complexity have been
proposed, at some point each of them seems to run into intrinsic limitations or
mutual disagreement. Two are the main objectives of the present work: (i) to
review some of the main approaches to complexity; and (ii) to suggest a
cost-based approach that, to a great extent, can be understood as an
integration of the several facets of complexity while keeping its meaning for
humans in mind. More specifically, it is poised that complexity, an inherently
relative and subjective concept, can be summarized as the cost of developing a
model, plus the cost of its respective operation. As a consequence, complexity
can vary along time and space. The proposal is illustrated respectively to
several applications examples, including a real-data base situation.
