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:
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 rowsFor 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 2024-04-02 07:12…
#> 7 5942a5b04c33f577946e4ccfbe490800 NA accepted species Drosophila melanogaster 2024-04-02 07:12…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 rowsAdding 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 2024-04-02 07:12:3…
#> 7 54135528 54126748 synonym species Hymenophyllum nigrescens Liebm. 2024-04-02 07:12:3…
#> 8 54135530 54126748 synonym species Mecodium nigricans (Presl ex Kl.) Copel. 2024-04-02 07:12:3…
#> 9 54135531 54126748 synonym species Sphaerocionium nigricans Presl ex Kl. 2024-04-02 07:12:3…
#> 10 54126748 NA accepted infraspecies Hymenophyllum myriocarpum var. nigrescens (Liebm.) Stolze 2024-04-02 07:12:3…
#> 11 54126749 NA accepted infraspecies Hymenophyllum trichophyllum var. buesii C. V. Morton 2024-04-02 07:12:3…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. 2024-04-02 07:12:37.110899
#> 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. NANotice 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. 2024-04-02 07:12:37.20248
#> 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. NAIf 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 2024-04-02 07:12:37.282529
#> 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. NAAutomatic 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. 2024-04-02 07:12:37.380827
#> 5 54115098 54115097 synonym species Cephalomanes densinervium (Copel.) Copel. 2024-04-02 07:12:37.363074Notice 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 2024-04…
#> 2 54133783 54115097 synonym species Trichomanes crassum Copel. Cephalomanes crassum (Copel.) M… 2024-04…
#> 3 54115097 NA accepted species Cephalomanes crassum (Copel.) M. G. Price NA 2024-04…
#> 4 54133784 54115098 synonym species Trichomanes densinervium Copel. Cephalomanes densinervium (Cope… 2024-04…
#> 5 54115098 NA accepted species Cephalomanes densinervium (Copel.) Copel. NA 2024-04…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.