A data quality system (DQS) in openLCA describes a pedigree matrix of m data quality indicators (DQIs) and n data quality scores (DQ scores). Such a system can then be used to assess the data quality of processes and exchanges by tagging them with an instance of the system D where D is a m * n matrix with an entry d_ij containing the value of the data quality score j for indicator i. As each indicator in D can only have a single score value, D can be stored in a vector d where d_i contains the data quality score for indicator i. The possible values of the data quality scores are defined as a linear order 1 ... n. In openLCA, the data quality entry d of a process or exchange is stored as a string like (3;2;4;n.a.;2) which means the data quality score for the first indicator is 3, for the second 2 etc. A specific value is n.a. which stands for not applicable. In calculations, these data quality entries can be aggregated in different ways. For example, the data quality entry of a flow f with a contribution of 0.5 kg and a data quality entry of (3;2;4;n.a.;2) in a process p and a contribution of 1.5 kg and a data quality entry of (2;3;1;n.a.;5) in a process q could be aggregated to (2;3;2;n.a.;4) by applying an weighted average and rounding. Finally, custom labels like A, B, C, ... or Very good, Good, Fair, ... for the DQ scores can be assigned by the user. These labels are then displayed instead of 1, 2, 3 ... in the user interface or result exports. However, internally the numeric values are used in the data model and calculations.



Inherited from Entity.@type


Inherited from RefEntity.@id


Inherited from RefEntity.name


Inherited from RefEntity.description


Inherited from RootEntity.category


Inherited from RootEntity.lastChange


Inherited from RootEntity.tags


Inherited from RootEntity.version




Python class stub

The snippet below shows the names of the properties of the corresponding Python class of the olca-schema package. Note that this is not the full class definition but just shows the names of the class and its properties.

class DQSystem:
  id: str
  category: str
  description: str
  has_uncertainties: bool
  indicators: List[DQIndicator]
  last_change: str
  name: str
  source: Ref
  tags: List[str]
  version: str