Multilevel data analysis using the example of data on research, development and other works performed in the interests of the Ministry of Emergencies of Russia
With large amounts of data as well as methods and tools for their analysis become available in the public domain, data analysis is increasingly being used to solve problems in all areas of human activity. However, the prevalence and ease of use of tools for analysis has certain negative aspects: the attitude to the analytical problem as a trivial procedure, ignoring the important theoretical limitations of mathematical methods, and insuffi ntly thorough verification of assumptions about the data. In this regard, there is a legitimate need to return practical analysis to the theoretical framework, if possible, inscribing it in the concept of solving more voluminous and complex problems, in the methodology of scientific research in general. The article proposes modeling the data analysis process as a multi-level system of interconnected procedures and data manipulations that differ in complexity, requirements and assumptions. The aim of the work is to structure the process of data analysis, regardless of the specific task and software tool for its solution. Thus, the object of research is the process of data analysis within the framework of the analytical problem, and the subject is the generalized structure of this process. In addition, arguments are given that justify the usefulness and content of this model. Each highlighted level of analysis is illustrated by examples of practical problems that are solved on the basis of a specific set of data on completed scientific works, their contents, and the team of authors. The model can be practically useful when planning a scientific research, calculating its complexity, determining the composition of the creative team, developing curricula.