The Biomedical and Clinical (BC) research domain has evolved significantly in the last decade, quickly becoming a data-intensive field that requires sophisticated databases and data analysis tools. The constant growth of BC data has given rise to the notion of data-driven decision making. BC institutions typically use a wide range of modern diagnostic equipment that produces various types of biomedical data. Such rich data can be used to greatly improve health care. However, the development of a robust BC decision support system (BCDSS) that is driven by the available data remains a major challenge. The expanded utilization of BCDSS has been limited by the fact that current available systems are developed based on different data models and data taxonomies. In addition, the increasing availability of genetic data and the association between genotype and various diseases necessitates an integrated model that incorporates a comprehensive view of biomedical and clinical information. Such an integrated model would make it possible to develop a robust and standard BC information systems (BCIS). Standardized databases of BCIS would certainly make it much easier to take full advantage of BCDSS as well as other advances in all domains of biomedical research. This paper presents the framework for human BC data structures and an attempt to create a flexible data model that supports the notion of healthcare IT standards and accommodates the design/development of domain-specific BC databases.