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dwctaxon has two major purposes, (1) editing and (2) validation of taxonomic data in Darwin Core (DwC) format. This vignette is about the former. Although you could use dwctaxon to build a taxonomic database from scratch, it is more likely you will be using it to modify an existing database, so we will focus on that kind of use-case.

We start by loading packages needed for this vignette:

library(dwctaxon)
library(tibble) # recommended for pretty-printing of tibbles

The data

dwctaxon comes with an example dataset dct_filmies, taxonomic data of filmy ferns (family Hymenophyllaceae). Let’s take a quick look at the data (you may need to scroll to the right of the frame with the code to see all the text):

dct_filmies
#> # A tibble: 2,451 × 5
#>    taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            
#>    <chr>    <chr>               <chr>           <chr>     <chr>                                     
#>  1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             
#>  2 54133783 54115097            synonym         species   Trichomanes crassum Copel.                
#>  3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price 
#>  4 54133784 54115098            synonym         species   Trichomanes densinervium Copel.           
#>  5 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. 
#>  6 54133786 54115100            synonym         species   Cephalomanes curvatum (J. Sm.) V. D. Bosch
#>  7 54133787 54115100            synonym         species   Cephalomanes javanica (Bl.) V. D. Bosch   
#>  8 54133788 54115100            synonym         species   Cephalomanes oblongifolium Presl          
#>  9 54133789 54115100            synonym         species   Cephalomanes zollingeri V. D. Bosch       
#> 10 54133790 54115100            synonym         species   Lacostea javanica (Bl.) Prantl            
#> # ℹ 2,441 more rows

For demonstration purposes, we will just use the first five rows:

filmies_small <- head(dct_filmies, 5)

Although DwC taxon format includes a large number of terms (columns)1, a typical database does not use all of them. dct_filmies only includes 5 columns. Their usage should be clear to most biologists, but two columns need more explanation. taxonID is a unique ID for each row (name), and acceptedNameUsageID is only provided for synonyms; it indicates the taxonID of the accepted name. For more information on DwC taxon format, see vignette("what-is-dwc").

The rest of the vignette will consist of modifying this dataset.

Adding rows

Adding rows by vector

dct_add_row() is used to add rows. The simplest way to do this is by specifying the new values as vectors (vectors of length 1 are recycled):

filmies_small |>
  dct_add_row(
    scientificName = c("Homo sapiens", "Drosophila melanogaster"),
    taxonomicStatus = "accepted",
    taxonRank = "species"
  )
#> # A tibble: 7 × 6
#>   taxonID                          acceptedNameUsageID taxonomicStatus taxonRank scientificName                            modified         
#>   <chr>                            <chr>               <chr>           <chr>     <chr>                                     <chr>            
#> 1 54115096                         NA                  accepted        species   Cephalomanes atrovirens Presl             NA               
#> 2 54133783                         54115097            synonym         species   Trichomanes crassum Copel.                NA               
#> 3 54115097                         NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA               
#> 4 54133784                         54115098            synonym         species   Trichomanes densinervium Copel.           NA               
#> 5 54115098                         NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. NA               
#> 6 be111923a2780f4931ca7fa4ed09a1b9 NA                  accepted        species   Homo sapiens                              2023-12-06 05:12…
#> 7 5942a5b04c33f577946e4ccfbe490800 NA                  accepted        species   Drosophila melanogaster                   2023-12-06 05:12…

Notice that although we did not specify taxonID or modified, these columns are automatically filled by default2; they can be turned off by setting the fill_taxon_id and stamp_modified arguments to FALSE.

The names of the new values should be valid DwC terms. You can see the terms available with dct_terms:

dct_terms
#> # A tibble: 47 × 2
#>    group term               
#>  * <chr> <chr>              
#>  1 taxon taxonID            
#>  2 taxon scientificNameID   
#>  3 taxon acceptedNameUsageID
#>  4 taxon parentNameUsageID  
#>  5 taxon originalNameUsageID
#>  6 taxon nameAccordingToID  
#>  7 taxon namePublishedInID  
#>  8 taxon taxonConceptID     
#>  9 taxon scientificName     
#> 10 taxon acceptedNameUsage  
#> # ℹ 37 more rows

Adding rows by dataframe

Adding rows with vectors as shown above works well if you only need to add a small number of rows. However, this could get unwieldy if you have a large number to add. In this case, you can instead add them via a dataframe.

The dataframe should have column names matching valid DwC taxon terms:

# Let's add some rows from the original dct_filmies
to_add <- tail(dct_filmies)

filmies_small |>
  dct_add_row(new_dat = to_add)
#> # A tibble: 11 × 6
#>    taxonID  acceptedNameUsageID taxonomicStatus taxonRank    scientificName                                              modified           
#>    <chr>    <chr>               <chr>           <chr>        <chr>                                                       <chr>              
#>  1 54115096 NA                  accepted        species      Cephalomanes atrovirens Presl                               NA                 
#>  2 54133783 54115097            synonym         species      Trichomanes crassum Copel.                                  NA                 
#>  3 54115097 NA                  accepted        species      Cephalomanes crassum (Copel.) M. G. Price                   NA                 
#>  4 54133784 54115098            synonym         species      Trichomanes densinervium Copel.                             NA                 
#>  5 54115098 NA                  accepted        species      Cephalomanes densinervium (Copel.) Copel.                   NA                 
#>  6 54126747 NA                  accepted        infraspecies Hymenophyllum myriocarpum var. endiviifolium (Desv.) Stolze 2023-12-06 05:12:2…
#>  7 54135528 54126748            synonym         species      Hymenophyllum nigrescens Liebm.                             2023-12-06 05:12:2…
#>  8 54135530 54126748            synonym         species      Mecodium nigricans (Presl ex Kl.) Copel.                    2023-12-06 05:12:2…
#>  9 54135531 54126748            synonym         species      Sphaerocionium nigricans Presl ex Kl.                       2023-12-06 05:12:2…
#> 10 54126748 NA                  accepted        infraspecies Hymenophyllum myriocarpum var. nigrescens (Liebm.) Stolze   2023-12-06 05:12:2…
#> 11 54126749 NA                  accepted        infraspecies Hymenophyllum trichophyllum var. buesii C. V. Morton        2023-12-06 05:12:2…

Note that in this case the taxonID already existed in the data to add, so it is not generated automatically.

Deleting rows

dct_drop_row() drops one or more rows by taxonID or scientificName.

For example, we can exclude the row for Cephalomanes atrovirens Presl by either using its scientificName (Cephalomanes atrovirens Presl) or its taxonID (54115096):

filmies_small |>
  dct_drop_row(scientificName = "Cephalomanes atrovirens Presl")
#> # A tibble: 4 × 5
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                           
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                    
#> 1 54133783 54115097            synonym         species   Trichomanes crassum Copel.               
#> 2 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price
#> 3 54133784 54115098            synonym         species   Trichomanes densinervium Copel.          
#> 4 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel.

filmies_small |>
  dct_drop_row(taxonID = "54115096")
#> # A tibble: 4 × 5
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                           
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                    
#> 1 54133783 54115097            synonym         species   Trichomanes crassum Copel.               
#> 2 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price
#> 3 54133784 54115098            synonym         species   Trichomanes densinervium Copel.          
#> 4 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel.

Since it looks up values by taxonID or scientificName, dct_drop_row() requires these to be unique and non-missing in the taxonomic database.

Of course, since the taxonomic database is a dataframe, you could also use other subsetting techniques like brackets in base R or dplyr::filter() from the tidyverse to delete rows.

Modifying rows

Identifying rows to modify

dct_modify_row() changes the values in an existing row.

Here, it is helpful to reiterate the purpose of the taxonID column: it is a unique identifier for each row (taxonomic name) in the data. So we will use taxonID to identify the row to change, then apply new values using other DwC terms.

# Change the status of Trichomanes crassum Copel. to "accepted"
filmies_small |>
  dct_modify_row(
    taxonID = "54133783", # taxonID of Trichomanes crassum Copel.
    taxonomicStatus = "accepted"
  )
#> # A tibble: 5 × 6
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            modified                  
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                     <chr>                     
#> 1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             NA                        
#> 2 54133783 NA                  accepted        species   Trichomanes crassum Copel.                2023-12-06 05:12:25.291032
#> 3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA                        
#> 4 54133784 54115098            synonym         species   Trichomanes densinervium Copel.           NA                        
#> 5 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. NA

Notice there were some additional automatic changes besides just taxonomicStatus. Since the new status is "accepted", dwctaxon automatically set acceptedNameUsageID (which indicates the taxonID of the accepted name for synonyms) to NA. This behavior can be disabled by setting the clear_usage_id argument to FALSE. We see the modified field has been updated as well.

However, it can be difficult for humans to keep track of which taxonID matches which name; typically, we think in terms of species names, not ID numbers. For that reason, you can also use scientificName instead of taxon_id to specify a row to modify3.

# Change the status of Trichomanes crassum Copel. to "accepted"
filmies_small |>
  dct_modify_row(
    scientificName = "Trichomanes crassum Copel.",
    taxonomicStatus = "accepted"
  )
#> # A tibble: 5 × 6
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            modified                  
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                     <chr>                     
#> 1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             NA                        
#> 2 54133783 NA                  accepted        species   Trichomanes crassum Copel.                2023-12-06 05:12:25.383649
#> 3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA                        
#> 4 54133784 54115098            synonym         species   Trichomanes densinervium Copel.           NA                        
#> 5 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. NA

If you provide both taxonID and scientificName, dwctaxon will identify the row with taxonID and apply scientificName as the new scientific name:

# Change the name of Trichomanes crassum Copel.
filmies_small |>
  dct_modify_row(
    taxonID = "54133783", # taxonID of Trichomanes crassum Copel.
    scientificName = "Bogus name"
  )
#> # A tibble: 5 × 6
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            modified                  
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                     <chr>                     
#> 1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             NA                        
#> 2 54133783 54115097            synonym         species   Bogus name                                2023-12-06 05:12:25.470769
#> 3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA                        
#> 4 54133784 54115098            synonym         species   Trichomanes densinervium Copel.           NA                        
#> 5 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. NA

Automatic re-mapping of synonyms

Another convenient automated behavior of dwctaxon is the ability to “re-map” synonyms. That is, if a previously accepted name (say, “A”) is changed to be the synonym of another name (say, “B”), all synonyms of “A” are also changed to be synonyms of “B”. Let’s see how this works with the example data:

# Change C. densinervium to a synonym of C. crassum
filmies_small |>
  dct_modify_row(
    scientificName = "Cephalomanes densinervium (Copel.) Copel.",
    taxonomicStatus = "synonym",
    acceptedNameUsage = "Cephalomanes crassum (Copel.) M. G. Price"
  )
#> # A tibble: 5 × 6
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            modified                 
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                     <chr>                    
#> 1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             NA                       
#> 2 54133783 54115097            synonym         species   Trichomanes crassum Copel.                NA                       
#> 3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA                       
#> 4 54133784 54115097            synonym         species   Trichomanes densinervium Copel.           2023-12-06 05:12:25.5568 
#> 5 54115098 54115097            synonym         species   Cephalomanes densinervium (Copel.) Copel. 2023-12-06 05:12:25.55426

Notice that two names were modified even though we only specified one; since Trichomanes densinervium Copel. was a synonym of Cephalomanes densinervium (Copel.) Copel., it also gets re-mapped to the accepted name Cephalomanes crassum (Copel.) M. G. Price

Filling columns

As described in vignette("what-is-dwc"), there are several terms in DwC that I call “term - termID” pairs, e.g., acceptedNameUsage and acceptedNameUsageID, parentNameUsage and parentNameUsageID, etc. Typically, one is an actual scientific name (e.g., for acceptedNameUsage, the accepted name of a synonym), and one is the taxonID of that name (e.g., for acceptedNameUsageID, the taxonID of the accepted name of a synonym). It is up to the manager of the database to choose whether to use either or both of the terms in the pair.

This sort of data is redundant and could be prone to error if entered manually, so dwctaxon can do it for us with dct_fill_col(). The easiest way to see how this works is with an example (you may need to scroll to the right to see the new column):

# Fill-in the acceptedNameUsage column with scientific names
filmies_small |>
  dct_fill_col(
    fill_to = "acceptedNameUsage",
    fill_from = "scientificName",
    match_to = "taxonID",
    match_from = "acceptedNameUsageID"
  )
#> # A tibble: 5 × 7
#>   taxonID  acceptedNameUsageID taxonomicStatus taxonRank scientificName                            acceptedNameUsage                modified
#>   <chr>    <chr>               <chr>           <chr>     <chr>                                     <chr>                            <chr>   
#> 1 54115096 NA                  accepted        species   Cephalomanes atrovirens Presl             NA                               2023-12…
#> 2 54133783 54115097            synonym         species   Trichomanes crassum Copel.                Cephalomanes crassum (Copel.) M… 2023-12…
#> 3 54115097 NA                  accepted        species   Cephalomanes crassum (Copel.) M. G. Price NA                               2023-12…
#> 4 54133784 54115098            synonym         species   Trichomanes densinervium Copel.           Cephalomanes densinervium (Cope… 2023-12…
#> 5 54115098 NA                  accepted        species   Cephalomanes densinervium (Copel.) Copel. NA                               2023-12…

The meaning of the arguments fill_to and fill_from I think are fairly clear: we are filling the acceptedNameUsage column with values from scientificName.

match_to and match_from are a bit trickier; they describe how to find the data for filling. Here, we are looking up acceptedNameUsage by matching acceptedNameUsageID (match_from) to taxonID (match_to).

Like I said, it’s easiest to figure out dct_fill_col() by trying it yourself.