Enhancing Scientometrics Prediction under Uncertainty: A DIKW-Based Framework and Methodological Synthesis

This paper analyzes the uncertainties present in predictive-oriented scientometric research and, through a literature review, organizes and categorizes information analysis tasks related to prediction under uncertain conditions. Furthermore, to better adapt to these tasks, we approach the issue from the perspective of the DIKW model and summarize various methods for handling uncertainty. Finally, we propose a research framework for conducting predictive -oriented scientometric studies in uncertain environments, using scenario analysis and signal analysis to dealing with uncertainty.