Technical term to describe/differentiate the structure of an instance by the number of samples per instance ('tuple' vs 'time series') Several terms are used to describe the structure of instances of a dataset. For example, an instance can be 'univariate' if it depends on only one variable or 'multivariate' if it depends on 2 or more variables. I wonder if there are technical terms to distinguish the structure of a, let's call it a 'tuple', and a 'time series' or 'sequence'.
Here are two examples that I am trying to describe or distinguish structurally:

The left example is a time series, where all 11 samples belong to one instance. The right example is a collection of 'tuples' (if that is the correct term), where each row represents a separate instance.
I always refer to the term 'tuple' here, because the concept seems similar to me with the record in a database or the representation of points from mathematics. I am not sure if 'time series' and 'tuple' are the correct terms to describe how many samples an instance consists of. The terms should be analogous to uni/multivariate to describe the number of features in an instance.
Hence my question:
If univariate/multivariate describes an instance in the horizontal, what terms are used to describe an instance vertically?
We have a Dataset
 Dataset has Instances
Instances can be a Vector Or a Sequence.

If it is a vector, It has Features
Examples - Image, Tabular data
If it is a Sequence, It has Time-steps**
Each Time-step can have Features i.e. Uni/Multi-Variate
Examples - Video, Audio, Time-series data

**When we use text-data as a sequence, we call the words as &quot;Tokens&quot;