A parent dataset is a dataset referred to by a Delta dataset and Child dataset as the source from which field values in the child dataset are to be inherited to the extent defined by the delta dataset. This inheritance mechanism enables efficient data management within LCA databases by establishing hierarchical relationships between datasets.
The parent dataset serves as a template or baseline that provides default values for a child dataset. Rather than duplicating all data when creating variations of a dataset, for example when representing the same activity in different geographical regions or time periods, the child dataset can inherit most of its data from the parent whilst only specifying the differences through the delta dataset. This approach significantly reduces data redundancy and maintenance burden.
The relationship works through three interconnected components. The parent dataset contains the baseline or reference data. The delta dataset specifies which fields from the parent should be inherited and which should be modified or replaced in the child. The child dataset is the resulting dataset that combines inherited values from the parent with modifications specified in the delta.
This inheritance structure is particularly valuable for maintaining consistency across related datasets. When updates are made to the parent dataset, these changes can automatically propagate to all child datasets that inherit those specific fields, ensuring that improvements or corrections are efficiently distributed throughout the database. However, any field explicitly defined in the delta dataset remains independent, allowing child datasets to maintain their specific variations.
The parent dataset concept is integral to modern LCA database architecture, especially in systems like ecoinvent, where it enables the creation of reference activity datasets that represent default or global average descriptions of activities. These reference datasets then serve as parents for more specific datasets representing particular geographical locations, time periods, or technological scenarios.
