Application of bibliometrics as a data mining technique for research prioritization

Abstract

The world is currently facing structural and deeply uncertain crises. Countries face paradoxical situations, where risks and opportunities, still poorly understood, coexist to accentuate uncertainty. Consequently, the challenges of growth and development are increasingly complex and interdependent. The role of science is becoming just as important in providing optimized solutions to these challenges. Thus, the reconciliation of scientific (and technical) capacities with socioeconomic needs is of crucial importance. This consists of specifying the scientific fields, subjects or questions where a reasonable research effort would have the best potential impact in meeting the needs, given the means available. In the face of complexity, this exercise must follow rigorous, but not strictly deterministic, approaches. In this sense, bibliometrics is often used to determine the state of knowledge in a field of research. Its ability to search large amounts of data and crosscheck analyses makes it a powerful decision-making tool. Used as a heuristic technique, it would stimulate, at different levels, the process of identifying and negotiating research priorities. Using the example of desalination research, the present work attempts to explore some uses of bibliometrics to inform the decision-making process in research prioritization. The theoretical underpinning of bibliometrics allows for heuristic approaches to data mining and provides an undeniable advantage in improving the effectiveness of traditional consensus-building methods for priority setting.