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The article deals with design patterns of relational databases that are used as storage systems of experimental data. The classification of these patterns based on their complexity and level of detail in the description of entities and their relations is given. For each pattern, specific features of its application in the process of data modeling are shown. Databases created on the basis of simple patterns are less adapted to changes. Their design corresponds only to a context of a solvable task. Databases created using more complex patterns have a more flexible design. It allows considering requirements which can arise in the future that minimizes need for redesign.

The article deals with the methodology of creation a universal data storage for applications oriented to the specialists who participate in scientific researches. It is assumed that the storage structure is not rigidly bound to any scientific domain, and it will be demanded in many projects related to the data accumulation, data analysis and processing. The proposed approach to the organization of the storage system is based on fundamental principles, concepts and technologies that used in the software design process. This process is based on the subject domain analysis and the detection criteria of commonality and variability which guarantee high abstraction level as one of the main tools for working with data.