YannByron commented on PR #9580:
URL: https://github.com/apache/paimon/pull/9580#issuecomment-5527387796

   > I suggest defining RoboMIND's native Paimon storage contract early, 
following the approach in #9529:
   > 
   > * Preserve original `master`/`puppet` fields, dtypes and image/depth 
payloads in `frames`; keep trajectory metadata in `episodes`.
   > * Add `tasks`, `annotations` and `calibrations` when provided by the 
source.
   > * Publish components under the same `BIGINT version_id` tag, with a 
`versions` manifest and `READY` written last.
   > * Treat canonical state/action and normalization statistics as explicitly 
derived data, not as the native schema.
   > 
   > Start with AgileX without assuming other RoboMIND variants share its 
layout or sampling axis. This can be a separate schema/ingestion change; the 
window API should stay generic and be tested against that native contract.
   
   
[robomind_agilex](https://github.com/apache/paimon/blob/master/paimon-python/pypaimon/sample/robomind_agilex.py)
 already defines an explicit Paimon storage contract for the RoboMIND AgileX 
dataset through `episode_schema`, `frame_schema`, and `feature_stats_schema`. 
It covers dataset metadata, ordered frame data, image/depth payloads, and the 
normalization data required for training.
   
   The current AgileX contract does not yet model `tasks`, `annotations`, or 
`calibrations`. These can be added when they are present in the AgileX source 
and required by a concrete consumer. I definitely agree that different datasets 
and variants should define their own table groups and table schemas according 
to their native contracts.
   
   The current `contiguous-window` dataset API addresses the requirements of 
the HDF5-based RoboMIND AgileX dataset while remaining extensible for future 
sources and modalities. I will first address the comments above. Afterwards, I 
will use PR https://github.com/apache/paimon/pull/9529 as a reference for 
adding a multi-table publication contract.


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