Requirements engineering plays a crucial role in the development process of an information system as it aims at providing a complete and accurate requirement specification. In the life cycle of a Data Repository (DR) such as a database or a data warehouse, the requirements are mainly used to define the conceptual model once they have been identified from the informal specification. In this paper, we study the interest of requirements in the other phases of the DR life cycle. As the data integration problem, handled in the Extract, Transform, Load (ETL) phase, comes from the heterogeneity of requirements, we introduce a requirement integration framework based on ontologies and a generic model to unify the used vocabularies and requirement languages. Then we propose an approach to check the consistency of the requirements, w.r.t. the integrity constraints defined on the logical schema using the formal B method. We also show that requirements help define appropriate access structures such as indexes and materialized views to optimize SQL queries of a DR. Our approach is based on transformation rules that identify important queries that will be executed on a DR directly from the requirements. The experiments conducted on the Star Schema Benchmark (SSB) confirm the interest of this approach for the selection of different optimization structures. Finally, we present the OntoReqTool that implements the previous functionality on top of the OntoDB/OntoQL platform.