Variable

Introduction

The variable application deals with the variables that can be ingested by Paricia, from what they are and what units they use to resources to help in the validation process. Specially important in this validation process will be:

• the maximum and minimum values that the variable can realistically take (these are mandatory fields)
• the maximum variability between consecutive data points
• the maximum statistical difference with respect the series allowed for a data point before it is considered an outlier
• the fraction of missing values that are allowed when calculating reports

Figure 1: UML diagram of the Variable app models.

Components

Unit

Unit of measurement with a name and a symbol.

Attributes:

Name	Type	Description
unit_id	AutoField	Primary key.
name	CharField	Name of the unit, eg. meters per second.
initials	CharField	Symbol for the unit, eg. m/s.

Variable

A variable with a physical meaning.

Such as precipitation, wind speed, wind direction, soil moisture, including the associated unit. It also includes metadata to help identify what is a reasonable value for the data, to flag outliers and to help with the validation process.

The nature of the variable can be one of the following:

• sum: Cumulative value over a period of time.
• average: Average value over a period of time.
• value: One-off value.

Attributes:

Name	Type	Description
variable_id	AutoField	Primary key.
variable_code	CharField	Code of the variable, eg. airtemperature.
name	CharField	Human-readable name of the variable, eg. Air temperature.
unit	ForeignKey	Unit of the variable.
maximum	DecimalField	Maximum value allowed for the variable.
minimum	DecimalField	Minimum value allowed for the variable.
diff_error	DecimalField	If two sequential values in the time-series data of this variable differ by more than this value, the validation process can mark this with an error flag.
outlier_limit	DecimalField	The statistical deviation for defining outliers, in times the standard deviation (sigma).
null_limit	DecimalField	The max % of null values (missing, caused by e.g. equipment malfunction) allowed for hourly, daily, monthly data. Cumulative values are not deemed trustworthy if the number of missing values in a given period is greater than the null_limit.
nature	CharField	Nature of the variable, eg. if it represents a one-off value, the average over a period of time or the cumulative value over a period

SensorInstallation

Represents an installation of a Sensor at a Station, which measures a Variable.

It includes metadata for installation and finishing date, as well as state (active or not).

Attributes:

Name	Type	Description
sensorinstallation_id	AutoField	Primary key.
variable	ForeignKey	Variable measured by the sensor.
station	ForeignKey	Station where the sensor is installed.
sensor	ForeignKey	Sensor used for the measurement.
start_date	DateField	Start date of the installation.
end_date	DateField	End date of the installation.
state	BooleanField	Is the sensor active?