Dataset granularities: Abstract vs. Versioned vs. Layer

When csv2rdf4lod converts tabular data to RDF, it also asserts metadata about the RDF using the conversion vocabulary. One type of metadata that it asserts is void:Dataset details, which lets us group collections of triples in a hierarchical fashion. csv2rdf4lod groups triples into three specific types of void:Dataset:

• conversion:AbstractDataset (subclass of void:Dataset)
  • conversion:VersionedDataset (subclass of void:Dataset that is a void:subset of conversion:AbstractDataset)
    • conversion:LayerDataset (subclass of void:Dataset that is a void:subset of conversion:VersionsedDataset)

So, the "largest" void:Dataset in the list above is conversion:AbstractDataset, and the "smallest" is conversion:LayerDataset.

As described in [the naming phase](Conversion process phase: name), three provenance-related aspects are used to organize any third party data that are retrieved. Each aspect is given a short, URI-friendly identifier string:

• source identifier - indicates the person/agent/organization that provided the data. For example, "epa-gov" provides a variety of datasets.
• dataset identifier - indicates the logical group of data. For example, the EPA distinguishes between the datasets "photochemical-assessment-monitoring-stations-pams" and "historical-radnet-air-quality-data".
• version identifier - indicates the version of a particular dataset. For example, you could have retrieved version "r23" - a designation from EPA themselves, or I could have retrieved version "2013-Mar-14" because the EPA didn't provide a version designation for what they provided.