Note from the Editor-in-Chief: Bridging Between Descriptive & Idiographic Research Approach and Nomothetic Research & Problem-Oriented Approach: A Necessity for the Sustainable Development of the Effectiveness of Scientometrics Studies

Editor-in-Chief Lecture

Author

Editor-in-Chief of Scientometrics Research Journal: Scientific Bi-Quarterly of Shahed University, And Professor, Department of Information Science and Knowledge Studies, Shahed University.

Abstract

More than a decade ago in 2012, when comparing descriptive and Nomothetic-oriented study approaches in the book "Introduction to Scientometrics (Foundations, Concepts, Relations & Origins)", I introduced descriptive informatics as the study and analysis of individual pieces of information, such as individual documents, topics, authors, readers, editors, journals, institutions, scientific fields, regions, countries, languages, and more. On the other hand, the "Nomothetic informetrics" approach was described as studies that aim to identify and introduce the existing rules and principles governing the flow of information.
Based on this perspective, the Descriptive research approach in scientometrics, which can also be introduced as an Idiographic approach, studies or discovers facts scientific processes, and specific variables without the ability to generalize and separate from general laws. Studying and monitoring the process of changes in variables such as researchers, universities, journals, countries, and the like can be considered a type of Descriptive & Idiographic research in scientometrics, which descriptively examines the dimensions and trends of change and evolution in certain variables. According to this viewpoint, the Descriptive & Idiographic research approach focuses on a comprehensive and in-depth understanding of changes in one or more variables and a specific case or a group of cases as an entity. The Descriptive & Idiographic research approach in scientometrics is often directly related to quantitative studies. This approach emphasizes the distinctiveness and uniqueness of the studied variables and phenomena. Instead of attempting to draw general conclusions that can be applied to a larger society, it aims to gain a profound understanding of the contexts in which the conditions and changes of variables and phenomena are studied. Questions such as "Which universities have managed to improve their position in international rankings?", "How has the position of one or more specific universities been in comparison with each other in various international rankings?", and "In which universities has the computer engineering department had a greater scientific impact?" are among the research questions proposed with Descriptive & Idiographic research approaches and can be addressed using the same approach.
In contrast, the Nomothetic approach is used in scientometrics to identify and extract rules and principles governing science and technology by generalizing to logical analogies or using mathematical models. The Nomothetic research approach, with an evaluative view, aims to establish specific frameworks during scientific interactions. This approach is employed in scientometrics to derive laws that explain the types or categories of phenomena present in the currents of science and technology. In the Nomothetic research approach, instead of focusing on the characteristics of specific variables, the scientometric researcher attempts to identify independent factors that cause changes in one or more variables or certain phenomena, thereby affecting a broader spectrum of the scientific community. The Nomothetic research approach, in a problem-oriented manner, seeks to identify principles, laws, and general theories, and discover consistent patterns and relationships across various cases or situations that can guide scientific behavior in a larger society or for a set of variables and cases. Therefore, the Nomothetic approach is reminiscent of the necessity for problem-oriented research, which has always been emphasized in scientific and academic circles. To conduct studies using the Nomothetic approach, relying solely on quantitative methods is insufficient; qualitative methods and approaches should also be incorporated. Hence, in the multiple influential studies of scientometrics, it is expected that the studies progress from the quantitative level to the qualitative and evaluative level. This qualitative approach emerges as a continuation of quantitative studies, enabling deeper analyses and the discovery of principles, laws, general theories, patterns, and relationships. Questions such as "What factors have contributed to improving the ranking of universities in international rankings?", "How can universities enhance their position in international ranking systems through policies and strategies? and "What is the correlation between research grant policies and laws and the ranking of universities in international ranking systems?”, are central problems that necessitate a Nomothetic research approach for resolution.
The focus of scientometrics on the Descriptive & Idiographic approach weakens the power of generalization, moves scientometrics away from its ultimate goal of playing a role as a support field for science and technology policy, damages the position of scientometrics, and makes it impossible to provide stable findings. To be more effective and deepen its findings, scientometrics must develop the level of analysis of its studies from the Descriptive & Idiographic approach to the Nomothetic research & Problem-oriented approach. By bridging between these two approaches, more stable, analytical results can be provided, offering deeper and more effective information to the science and technology policy-making community. Undoubtedly, more reflection and answering questions like this can lead the way in this direction: How is it possible to implement studies that simultaneously use Descriptive & Idiographic and Nomothetic research & Problem-oriented approaches?  How can students' dissertations and theses, and researchers' scientometrics research projects be led to using these two approaches simultaneously?  What is the best solution to create a bridge between these two approaches in scientometric studies?