This document proposes an information-theoretic framework for flow visualization using information-aware streamline placement. It calculates an entropy field based on vector values to detect regions of interest. Streamlines are seeded in high entropy areas and pruned in low entropy regions. The method places initial seeds using a diamond template and conditional entropy. It generates streamlines using streamline diffusion and interpolation. Results on 2D and 3D examples show the streamlines capture key flow features compared to traditional seeding methods. Future work includes considering spatial distribution and vector magnitudes in the entropy calculation.