Consistency of the term used to express data point kind, instrument kind

What are you trying to achieve?

When the specification and the SDK documentation mention gauge, histogram, counter, and exponential histogram, it uses different terms to refer to the same concept. After searching the spec, I see the following terms have been used:

1. Value type
2. Data point type
3. Data point kind
4. Basic point kind
5. Instrument kind
6. Instrument type

It would be good to use the same term consistently throughout the specification (data-model.md) and the SDK documentation (sdk.md).

Additional context.

Quotes	URL
... Value type of the point (integer, floating point, etc) - here "value type" refers to whether the value is integer or float, and in the next sentence, "value type" refers to gauge, counter, histogram.	data-model.md#L248-L254
The primary data of each timeseries are ordered (timestamp, value) points, with one of the following value types: Counter (Monotonic, Cumulative), Gauge, Histogram, Exponential Histogram	data-model.md#L248-L254
The data point type (e.g. Sum, Gauge, Histogram ExponentialHistogram, Summary)	data-model.md#L283
Within certain data point types (e.g., Sum and Gauge) there is variation permitted in the numeric point value	data-model.md#L302-L303
The basic point kinds are: Sum, Gauge, Histogram, Exponential Histogram	data-model.md#L351-L363
OTLP does not map 1:1 from its point types into timeseries points	data-model.md#L366
The Default Aggregation informs the SDK to use the Instrument kind to select an aggregation	sdk.md#L415-L422
The monotonicity of the aggregation is determined by the instrument type	sdk.md#L433-L440
If the potential conflict involves instruments that can be distinguished by a supported View selector (e.g., instrument type)	sdk.md#L685-L686