The paper addresses the challenge of designing effective systems for ontology-based data access, where the goal is to link existing data sources to an ontology. The authors propose a new logic, *DL-Lite$_A$*, which is a member of the *DL-Lite* family of Description Logics. This logic distinguishes between objects and values, attributes, and roles, allowing for more expressive power while maintaining efficient reasoning. The paper also introduces a mapping language to handle the impedance mismatch between data sources and the ontology, enabling the creation of new object identifiers from data values. Additionally, a novel query answering method is presented, which combines reasoning at the ontology level with mechanisms for handling mappings and accessing data sources efficiently. The method involves expanding queries according to the ontology, unfolding them to translate into queries over the data sources, and evaluating these queries using a relational database management system (DBMS). The paper concludes with a detailed technical framework for linking relational data to *DL-Lite$_A$* ontologies, emphasizing the practicality and efficiency of the proposed approach.The paper addresses the challenge of designing effective systems for ontology-based data access, where the goal is to link existing data sources to an ontology. The authors propose a new logic, *DL-Lite$_A$*, which is a member of the *DL-Lite* family of Description Logics. This logic distinguishes between objects and values, attributes, and roles, allowing for more expressive power while maintaining efficient reasoning. The paper also introduces a mapping language to handle the impedance mismatch between data sources and the ontology, enabling the creation of new object identifiers from data values. Additionally, a novel query answering method is presented, which combines reasoning at the ontology level with mechanisms for handling mappings and accessing data sources efficiently. The method involves expanding queries according to the ontology, unfolding them to translate into queries over the data sources, and evaluating these queries using a relational database management system (DBMS). The paper concludes with a detailed technical framework for linking relational data to *DL-Lite$_A$* ontologies, emphasizing the practicality and efficiency of the proposed approach.