  We propose a novel framework to facilitate the on-demand design of
data-centric systems by exploiting domain knowledge from an existing ontology.
Its key ingredient is a process that we call focusing, which allows to obtain a
schema for a (possibly knowledge-enriched) database semi-automatically, given
an ontology and a specification of the scope of the desired system. We
formalize the inputs and outputs of focusing, and identify relevant
computational problems: finding a schema via focusing, testing its consistency,
and answering queries in the knowledge-enriched databases it produces. These
definitions are fully independent of the ontology language. We then instantiate
the framework using selected description logics as ontology languages, and
popular classes of queries for specifying the scope of the system. For several
representative combinations, we study the decidability and complexity of the
identified computational problems. As a by-product, we isolate (and solve)
variants of classical decision problems in description logics, that are
interesting in their own right.
