We propose a novel use of ontologies to aid the on-demand design of data-centric systems. By means of a process that we call focusing, a schema for a (possibly knowledge-enriched) database can be obtained semi-automatically from an existing 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 independent from the ontology language. We then study focusing for 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) mixed variants of the classical satisfiability and entailment problems, where selected predicates are required to have finite extension, as well as the nullability problem, which is closely related to query emptiness.