The field of complex system analysis and visualization is moving towards the development of more sophisticated and principled tools for comparing and understanding complex systems. Researchers are focusing on creating innovative methods for visualizing and analyzing multivariate, multiscale data, such as turbulent flows and process communication latency. These new approaches are enabling scientists to better comprehend the interactions between multiple fields and length scales in complex systems. Notable papers in this area include: PCLVis, which provides a framework for analyzing process communication latency events in large-scale simulations. Glyph-Based Multiscale Visualization of Turbulent Multi-Physics Statistics, which introduces a novel local spatial statistical visualization of flow fields across multiple fields and turbulence scales. ClustOpt, which proposes a clustering-based approach for representing and visualizing the search dynamics of numerical metaheuristic optimization algorithms.