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It should be kept in mind that different services have different data needs, and might need an expanded dataset in order to function. Still, sorting data points into different bundles makes the data use cases clearer compared to listing individual data points. Apart from these first data bundles, we should also consider different categories based on data sensitivity, privacy and regional laws.
Most services need data points from across different technical categories. E.g. a service might need charging.state_of_charge and engine.oil_temperature. It could be said that they need to access two different data categories. It could also be said that they need to access a "Container" that includes these two different data points. To build up consistency inside companies, but also across, it makes sense that common use-cases have pre-defined containers. These are typically called "Data bundles" or "Data buckets", which is like a template of a container that has other meta information attached to it like purpose of use, pricing and rate limits.
(When we speak about transferring measured values that are bundled together, note the related definition of a Snapshot)
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