Filling Out the Uniformly Sampled Class
The <Uniformly_Sampled> class can be used in any tabletype class (like <Table_Character>) when the table contains records which are uniformly spaced in some dimension (time, wavelength, distance, etc.). This class is used to define that dimension and interval rather than including an additional field in each row to hold the value explicitly.

For additional explanation, see the PDS4 Standards Reference, or contact your PDS node consultant.
Following are the attributes and subclasses you'll find in <Uniformly_Sampled>, in label order.
Note that in the PDS4 master schema, all classes have capitalized names; attributes never do.
Contents
<sampling_parameter_name>
REQUIRED
The name of the dimension of sampling (wavelength, time, etc.)
<sampling_parameter_interval>
REQUIRED
Distance between records in units of the sampling parameter. So if you're sampling in time the interval might be 100 milliseconds, for example, so the value you would put here is 100.
<sampling_parameter_unit>
REQUIRED
The unit associated with the sampling_parameter_interval, first_sampling_parameter_value, and last_sampling_parameter_value, following. In the previous example, this would be ms.
<first_sampling_parameter_value>
REQUIRED
The value of the sampling parameter at the point where the data of the first record were recorded. The data dictionary specifically indicates that the minimum sampling parameter value corresponds to the first datum of the sampling interval  so it directly corresponds to the first sample.
The units for this value are in the sampling_parameter_unit attribute, above.
<last_sampling_parameter_value>
REQUIRED
The value of the sampling parameter at the point where the data of the last record were recorded.
The units for this value are in the sampling_parameter_unit attribute, above.
<sampling_parameter_scale>
REQUIRED
This is actually the type of the scale. It must be one of the standard values Exponential, Linear, or Logarithmic. If you specify a type of Exponential, you must also include a <sampling_parameter_base> attribute. Logarithmic scales are assumed to be base 10 unless a <sampling_parameter_base> attribute is present with a different value.
<sampling_parameter_base>
OPTIONAL
This attribute is required to be present and greater than 0.0 for exponential sampling scales. It is optional (but still required to be greater than 0.0) for logarithmic scales (base 10 is assumed if this attribute is not present). It is prohibited if the scale is linear.