The 4th DataCV Workshop focuses on advancing data-centric perspectives in computer vision, shifting attention from algorithm-centric research to the analysis and understanding of vision datasets. We aim to explore dataset-level properties, representations, and similarities, as well as challenges in bias, fairness, and generalization. Topics include evaluating vision-language models, improving dataset quality through simulation, and reducing reliance on labeled data. The workshop encourages research on how dataset insights can guide model development, performance prediction, and ethical considerations. By fostering discussion and innovation in dataset analysis, DataCV promotes more robust, generalizable, and responsible vision systems.