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@@ -20,6 +20,8 @@ See [aind-file-standards](https://github.com/allenneuralDynamics/aind-file-stand
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Rigs are responsible for generating the [acquisition.json](https://aind-data-schema.readthedocs.io/en/latest/acquisition.html) as well as any optional files (e.g., quality_control.json), if your situation requires it. You can either generate these metadata files directly or use the extractor/mapper pattern to extract necessary metadata on the rig and then map it in the cloud to aind-data-schema.
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References to the instrument in the `acquisition.json` must be consistent with the corresponding information in the [`instrument.json`](https://aind-data-schema.readthedocs.io/en/latest/instrument.html). See the [Instrument and Acquisition section in the AIND Data Schema docs](https://aind-data-schema.readthedocs.io/en/latest/validation.html) for details. Scientists collecting data should work closely with engineers maintaining their systems to ensure that this metadata remains consistent and will validate.
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#### Extractor / Mapper Pattern
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If you can't generate your aind-data-schema formatted metadata on your rig, you can use what we call the “extractor/mapper” pattern. We refer to the code on the rig that extracts metadata from data files as the extractor. We prefer for you to maintain this code in [aind-metadata-extractor](https://github.com/AllenNeuralDynamics/aind-metadata-extractor/) but you can also maintain it yourself. The code that takes the extractor output and transforms it to aind-data-schema is called the mapper. Scientific computing will help develop the mapper as well as maintain it, you are responsible for your extractor. The key to the extractor/mapper pattern is the data contract that defines the extractor output. The data contract must be a pydantic model or JSON schema file and must live in the [aind_metadata_extractor.models](https://github.com/AllenNeuralDynamics/aind-metadata-extractor/tree/main/src/aind_metadata_extractor/models) module.
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