Introduction: Storage and usage of research data become more sophisticated as their quantity and diversity grow. Research data have a number of features which do not allow you to copy the approaches and tools used in commercial or governmental data-processing facilities. Providing researchers with specialized tools for working with data is an urgent task in research management. Purpose: Identifying and describing the basic principles for working with research data, the processes and stages of this work, the mechanisms for implementing the principles and solving the problems of organizing the storage and usage of research data. Results: We review and discuss the principles on which the storage and usage of research data can be based, including the FAIR Data Principles. The main goal of organizing the work with research data and the central focus of its principles is the effective use and reuse of this data. We present a hierarchy of mechanisms which can be applied when working with research data for solving scientific and organizational problems. The main processes and lifecycle stages of scientific data and research processes based on them are listed in the article. A number of well-known models of such lifecycles are considered. It is proposed, instead of trying to build a universal model, to use or create models based on the presented list of stages for specific cases or classes of data-driven research. Practical relevance: The hierarchy of concept classes developed in the work for the field "Organizing the storage and usage of scientific data" will be used as an ontology core, and for the development of regulatory documents, recommendations and information systems supporting data-driven research.