During data manipulation, the combination of attributes through the relational join operator is needed. Introduction A common methodology that is used up to today in the design of relational databases is the specification of a set of attributes in (usually) one and universal relation, the specification of a set of functional dependencies among these attributes and the decomposition of the set of attributes into smaller relations which consist of subsets of the original set of attributes, in order to eliminate update anomalies and reduce data redundancy. In this way, the development process consisting in conceptual design (ER), transformation to Logical Relational Schema, usage of SQL for data manipulation/retrieval and the reverse steps to present the results in the conceptual level is simplified by conceptual design (ER), transformation to CAL and the usage of CUDL for direct manipulation/retrieval of real world (conceptual) structures. Consequently, the resulting more powerful and composite data can be directly maintained with the CUDL language. This set consists of 5 rules, proposed in a previous work by us and, in this paper, it is extended with an extra rule that deals with specific situations appearing in practical applications. We demonstrate that a database modelled by Entity-Relationship (ER) diagrams can be directly expressed to the CUDL Abstraction Level (CAL), by a set of rules for direct transformation of ER diagrams to CAL. The Conceptual Universal Database Language (CUDL) is such a language that leads to more abstract database design levels. However, more powerful models need query and manipulation languages that can handle the features of the new composite data types. This model provides more powerful and composite data types, as those of the real world. In this paper, we discuss another approach, where the Information System designers would be able to depict the real world in a database model directly. Vassilakopoulos 2 1 Department of Informatics Technological Educational Institute of Athens, Greece 2 Department of Computer Science and Biomedical Informatics University of Central Greece, Lamia, Greece The simplicity of the relational model types affects Information Systems design. Databases were defi ned by Frawley et al.Database Design with Real-World Structures Nikitas N. 2.1 The Origins of Medical Databases Lindberg (1979) described the degrees of diffi culty in the development of medical innovations in the grades of their complexity: (1) the easiest was the automation of a simple function such as providing a patient's billing for services (2) more diffi cult was the automation of a more complex function such as collecting and storing a patient's medical history (3) very diffi cult was constructing a very complex function such as a medical database and (4) the most diffi cult was developing the highly complex medical information and database-management system for a hospital, as Starr (1982) had aptly ranked the hospital to be the most complex organizational structure created by man. For an unusual or a complex medical problem, physicians may refer the patient to appropriate clinical specialists, and may also review evidence-based reports of appropriate therapies by consulting relevant medical literature and bibliographic databases. After reviewing the information received from these services, physicians usually arrive at a more certain diagnosis, and then prescribe appropriate treatment. To confi rm a preliminary diagnosis and to rule-out other possible diagnoses, physicians refer the patients for selected tests and procedures that usually involve the clinical laboratory, radiology, and other clinical-support services. In the 2000s, as in the 1900s, physicians continue to initiate this learning process by taking a history of the patient's medical problems, performing a physical examination of the patient, and then recording the history and physical examination fi ndings in the patient's medical record. Osler, to study and learn from their patients and from the medical records of their patients, in order to improve their knowledge of diseases. Since the early 1900s physicians have followed the teachings of the famed clinician, W.
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