A data constraint which contains a DataKeySet allows for the definition of constrained keys or wildcard keys, for example
Constrained Series
A.UK.EMP.M
A.FR.EMP.M
Constrained Wildcard Series
A..EMP.M
The problem comes when the constraint needs to constrain mulitple values in a dimension but not all values (i.e. a wildcard is too wide a scope) For example:
//constrain a set of countries for employed male
A.UK.EMP.M
A.FR.EMP.M
A.DE.EMP.M
//constrain a set of countries for employed female
A.UK.EMP.F
A.FR.EMP.F
A.DE.EMP.F
When mulitple dimensions are involved with multiple values in each dimension the number of series grows as a cartesian product. It is better to have a series constraint with multiple values in the key part which can collapse multiple rules into one:
A.UK+FR+DE.EMP.M+F
The SDMX Schmea defines a Key as having 1-many KeyValue, and a KeyValue is an id/value pair. If the KeyValue was modified to allow one or more values this use case would be supported.
A data constraint which contains a DataKeySet allows for the definition of constrained keys or wildcard keys, for example
Constrained Series A.UK.EMP.M
A.FR.EMP.M
Constrained Wildcard Series A..EMP.M
The problem comes when the constraint needs to constrain mulitple values in a dimension but not all values (i.e. a wildcard is too wide a scope) For example:
//constrain a set of countries for employed male
//constrain a set of countries for employed female
When mulitple dimensions are involved with multiple values in each dimension the number of series grows as a cartesian product. It is better to have a series constraint with multiple values in the key part which can collapse multiple rules into one:
A.UK+FR+DE.EMP.M+FThe SDMX Schmea defines a Key as having 1-many KeyValue, and a KeyValue is an id/value pair. If the KeyValue was modified to allow one or more values this use case would be supported.