I checked the licences and videos of public robot datasets: here's what I found

An open-source checker called rdq found that 56.5% of the 3,000 most-downloaded LeRobot robot datasets carry apache-2.0 on an unedited template card, likely the upload tool's default rather than the owner's choice, according to a Hugging Face forum write-up by developer rs1g6r. Of 304 datasets tracing to a known public source, 200 declare a different licence from the original, mostly CC BY 4.0 data relabelled apache-2.0 or MIT, and on LeBoard only 9 of 91 datasets carry a licence matching their source while 4 have no dataset card. A frame-by-frame video check of about 4,600 episodes in 20 datasets surfaced a second camera freezing at the start of six episodes, a camera moved mid-dataset, and later a black-rendering episode in zima-robot/liftplace-ee-xyz-500-v2 and two video-less episodes plus one duplicate in lerobot/berkeley_rpt, with 14 false alarms fixed and turned into tests.

rs1g6r https://discuss.huggingface.co/u/rs1g6r 1 Robot learning runs on shared data, and most of us download a dataset, check that it loads, and start training. I built an open-source checker, rdq, to look at what we usually skip: whether we’re allowed to use the data, and whether the camera footage is usable. Full write-up: rdq/docs/findings-2026-10.md at main · s1g6r/rdq · GitHub https://github.com/s1g6r/rdq/blob/main/docs/findings-2026-10.md Licences 3,000 most-downloaded LeRobot datasets : - 56.5% carry apache-2.0 on an unedited template card, most likely the upload tool’s default rather than the owner’s choice. - 200 of the 304 that trace to a known public dataset declare a different licence from the original, mostly CC BY 4.0 data relabelled apache-2.0 or MIT still usable, but the credit requirement drops off on paper . - On LeBoard, 9 of 91 datasets carry a licence that matches their source, and 4 have no dataset card. Video every frame of about 4,600 episodes in 20 datasets, every flag checked by eye : a second camera that freezes at the start of six episodes, a camera moved halfway through a dataset, and a few near-identical 5-second episodes with no task in them. I’ve told the owners. Update: the owners say those short clips are deliberate no-bottle examples, so that one isn’t a defect. rdq can flag an episode as unusual, not tell you why. Three false alarms came up on the way and were fixed; the write-up explains them. Try it: pip install "rdq video @ git+https://github.com/s1g6r/rdq" , then rdq check owner/dataset --video-full . There’s also a no-install licence check as a Space rs1g6r/rdq . If you maintain, collect or buy robot data, I’d like to hear which checks you wish existed. Send me a dataset or a sample delivery and I’ll send back the report. rs1g6r https://discuss.huggingface.co/u/rs1g6r 2 Update, five days on: - rdq is on PyPI now: pip install "rdq video " , then rdq check owner/dataset --video-full . - I ran the frame-by-frame check on about 100 more datasets, including 62 of LeBoard’s at the versions it pins. Two more problems held up and were reported to the owners: an episode that renders black in both cameras of zima-robot/liftplace-ee-xyz-500-v2 , and in lerobot/berkeley rpt two episodes with no video at all the file ends where the episode should start plus one episode that repeats another. - False alarms are at 14 now from 3 , each checked by eye, fixed and turned into a test: a humanoid’s stereo head cameras read as swapped, a precise industrial robot whose repeat takes looked like copies, a white table read as a covered lens, a 1 fps camera whose scripted takes matched over an empty table. The write-up is updated with all of it: rdq/docs/findings-2026-10.md at main · s1g6r/rdq · GitHub https://github.com/s1g6r/rdq/blob/main/docs/findings-2026-10.md nootxlm https://discuss.huggingface.co/u/nootxlm 3 The check I’d most want is the one that separates a defect from a deliberate example: compare each flagged episode’s frame change against its own action and state log. If the robot moved on paper while the frame stayed frozen, black, or missing, that could be a capture defect; if both stayed still, it is more likely an intentional idle or no-task clip — that one comparison could turn several of the eye-checked false alarms into an automatic verdict.