The TrackDLO data release supports the paper, "TrackDLO: Tracking Deformable Linear Objects Under Occlusion with Motion Coherence," published in Robotics and Automation: Letters. The TrackDLO data release includes the raw image and depth data for tracking Deformable Linear Objects (DLOs) under tip occlusion, large-scale mid-section occlusion, and self-occlusion. The released data are Robot Operating System (ROS1) bag files containing raw color images and point clouds. The data were collected using a static Intel Realsense d-435 RGB-D camera while DLOs in the field of view of the camera were manipulated. The data can be used to benchmark the performance of future vision-only DLO tracking algorithms in several manipulation scenarios relevant to DLOs and to verify existing vision-only DLO tracking algorithms. Please see the RA-L paper, the code repository on GitHub, the conference presentation, and the supplementary demonstration video for more information.