Domain Model

Initial domain model

classDiagram
    User --> "*" DataSource: owns
    DataSource <-- "*" Reading: values from
    DataSource --> "0..1" Location

    class User {
        email: EmailStr
        username: string
        created_at: Datetime
        updated_at: Datetime

    }
    class DataSource {
        name: string
        description: string
        owner: User
        data: Map[string,string]
        units: string[*]
    }
    class Reading {
        timestamp: Datetime
        created_by: User
        values: Map[string,Any]
    }
    class Location {
        name
        address
        coordinates?
    }

Loading

The id attribute of model classes is not part of the domain model, hence not shown.

In DataSource the data is a dict of measurement_name: unit_name for values read from the data source. Use a dict even if there is only one value per reading, e.g. electric meter.

In Reading the values is a dict of measurement_name: value, where value is the actual (numeric) value of some measurement, and measurement_name matches one of the keys defined in the corresponding DataSource data dict.

The timestamp is the date/time of the reading value, which may not be same as when the values were entered (created_at).

Reading.values may be implemented as a dict (Map), with value names as keys.

Possible Names for the Readings Value Descriptor Field in DataSource

Suggested Name	Rationale
value_units	Clear, concise. Maps "value name" → "unit".
units_by_name	Emphasizes that units are keyed by value name.
measurement_units	Semantically clear; aligns with concept of "measured values and their units".
reading_units	Suitable if each value is a readout from a device or sensor.
value_definitions	General but semantically appropriate if additional metadata might be added.
named_units	Highlights that each unit is tied to a named value.
metrics	Very concise; common in telemetry contexts, though slightly abstract.
reading_format	Suggests how readings are structured; suitable if used for validation.
value_schema	Indicates both the names and expected units, with potential extensibility.
reading_schema	Same intent as value_schema.
schema	If the dict defines the structure of readings, this is a semantically rich choice.

Which to Choose?

• Simplicity: If the dictionary will remain a simple mapping of name -> unit, then value_units is ideal.
• Clarity & Extensibility: value_units or value_schema strike a good balance between conciseness and semantic clarity.
• **Extensibility: value_schema` if there's potential to include more metadata per value, e.g., description, valid range.