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In old version of verify_taxa the df output duplicates_taxa contained taxa from different checklists which with same scientific name.
In new verify_taxa(), I propose to use duplicates_taxa to collect all taxa which point to same bb_key-bb_acceptedKey.
Example. The taxa here below would be in duplicates_taxa:
taxonKey
scientificName
bb_key
bb_acceptedKey
1
A
10
15
2
B
10
15
3
C
10
15
Drawback of this implementation: taxa without match to GBIF Backbone would be not included. So the following two taxa which are very likely the same species, would be not returned in duplicates_taxa:
taxonKey
scientificName
bb_key
bb_acceptedKey
4
E
NA
NA
5
E
NA
NA
I can live with that 😄 @peterdesmet : you too? It is actually a question about the meaning we want to give to the expression "duplicates taxa". As we use now a key-triplets (taxonkey - bb_key - bb_acceptedKey) to identify unique taxa instead of names, I think using bb_key - bb_acceptedKey sounds to be the best option.
The text was updated successfully, but these errors were encountered:
In old version of
verify_taxa
the df outputduplicates_taxa
contained taxa from different checklists which with same scientific name.In new
verify_taxa()
, I propose to useduplicates_taxa
to collect all taxa which point to samebb_key
-bb_acceptedKey
.Example. The taxa here below would be in duplicates_taxa:
Drawback of this implementation: taxa without match to GBIF Backbone would be not included. So the following two taxa which are very likely the same species, would be not returned in
duplicates_taxa
:I can live with that 😄 @peterdesmet : you too? It is actually a question about the meaning we want to give to the expression "duplicates taxa". As we use now a key-triplets (
taxonkey
-bb_key
-bb_acceptedKey
) to identify unique taxa instead of names, I think usingbb_key
-bb_acceptedKey
sounds to be the best option.The text was updated successfully, but these errors were encountered: