finch – parse Darwin Core files

December 23, 2016
By

(This article was first published on rOpenSci Blog - R, and kindly contributed to R-bloggers)

finch has just been released to CRAN (binaries should be up soon).

finch is a package to parse Darwin Core files. Darwin Core is:

a body of standards. It includes a glossary of terms (in other contexts these might be called properties, elements, fields, columns, attributes, or concepts) intended to facilitate the sharing of information about biological diversity by providing reference definitions, examples, and commentaries. The Darwin Core is primarily based on taxa, their occurrence in nature as documented by observations, specimens, samples, and related information. … The Simple Darwin Core [SIMPLEDWC] is a specification for one particular way to use the terms – to share data about taxa and their occurrences in a simply structured way – and is probably what is meant if someone suggests to "format your data according to the Darwin Core".

Let's use DwC for short going forward.

GBIF (Global Biodiversity Information Facility) is the biggest holder of biodiversity data. When you request
data in bulk format from GBIF they call give it to you in what's called a Darwin Core Archive, or
DwC-A. GBIF has a validator for DwC-A files as well: http://tools.gbif.org/dwca-validator/

One of our most used packages is probably rgbif, a client to interact with GBIF's web services.
There's a series of functions in rgbif to request data in bulk format (see functions starting
with occ_download), and from this you get a DwC-A file. This is where finch comes in:
it can parse these DwC-A files into something useable inside R.

Installation

install.packages("finch")
# or from source if binary not available yet
install.packages("finch", type = "source")
library("finch")

To parse a simple darwin core file like



 
  urn:catalog:YPM:VP.057488
  PhysicalObject
  2009-02-12T12:43:31
  en
  FossilSpecimen
  YPM
  VP
  VP.057488
  1
  
  North America
  United States
  US
  Montana
  Garfield
  Tyrannosourus rex
  Tyrannosourus
  rex
  Creataceous
  Creataceous
  Late Cretaceous
  Late Cretaceous
 

This file is in this package as an example file, get the file, then simple()

file <- system.file("examples", "example_simple_fossil.xml", package = "finch")
out <- simple_read(file)

Index to meta, dc or dwc

out$dc
#> [[1]]
#> [[1]]$type
#> [1] "PhysicalObject"
#> 
#> 
#> [[2]]
#> [[2]]$modified
#> [1] "2009-02-12T12:43:31"
#> 
#> 
#> [[3]]
#> [[3]]$language
#> [1] "en"

Parse Darwin Core Archive

To parse a Darwin Core Archive like can be gotten from GBIF use dwca_read()

dwca_read() can parse a DwC-A file as a directory, zipped file, or from a URL.

There's an example Darwin Core Archive:

file <- system.file("examples", "0000154-150116162929234.zip", package = "finch")
(out <- dwca_read(file, read = TRUE))
#> 
#>   Package ID: 6cfaaf9c-d518-4ca3-8dc5-f5aadddc0390
#>   No. data sources: 10
#>   No. datasets: 3
#>   Dataset occurrence.txt: [225 X 443]
#>   Dataset multimedia.txt: [15 X 1]
#>   Dataset verbatim.txt: [209 X 443]

List files in the archive

out$files
#> $xml_files
#> [1] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/meta.xml"    
#> [2] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/metadata.xml"
#> 
#> $txt_files
#> [1] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/citations.txt" 
#> [2] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/multimedia.txt"
#> [3] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/occurrence.txt"
#> [4] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/rights.txt"    
#> [5] "/Library/Frameworks/R.framework/Versions/3.3/Resources/library/finch/examples/0000154-150116162929234/verbatim.txt"  
...

High level metadata for the whole archive (printing a subset for brevity)

out$emlmeta
#> 
#>   
#>     GBIF Occurrence Download 0000154-150116162929234
#>     
#>       
#>         GBIF Download Service
#>       
#>     
#>     
#>       
#>         GBIF Download Service
#>       
#>     
#>     
#>       OZCAM (Online Zoological Collections of Australian Museums) Provider
#>       http://www.ozcam.org.au/
#>       CONTENT_PROVIDER
#>     
#>     
#>       
...

High level metadata for each data file, there's many files, but we'll just look at one

hm <- out$highmeta
head( hm$occurrence.txt )
#>   index                                        term delimitedBy
#> 1     0         http://rs.gbif.org/terms/1.0/gbifID        
#> 2     1           http://purl.org/dc/terms/abstract        
#> 3     2       http://purl.org/dc/terms/accessRights        
#> 4     3      http://purl.org/dc/terms/accrualMethod        
#> 5     4 http://purl.org/dc/terms/accrualPeriodicity        
#> 6     5      http://purl.org/dc/terms/accrualPolicy        

You can get the same metadata as above for each dataset that went into the tabular dataset downloaded

out$dataset_meta[[1]]

View one of the datasets, brief overview.

head(out$data[[1]][,c(1:5)])
#>      gbifID abstract accessRights accrualMethod accrualPeriodicity
#> 1  50280003       NA                         NA                 NA
#> 2 477550574       NA                         NA                 NA
#> 3 239703844       NA                         NA                 NA
#> 4 239703843       NA                         NA                 NA
#> 5 239703833       NA                         NA                 NA
#> 6 477550692       NA                         NA                 NA
names(out$data[[1]])[1:20]
#>  [1] "gbifID"                "abstract"             
#>  [3] "accessRights"          "accrualMethod"        
#>  [5] "accrualPeriodicity"    "accrualPolicy"        
#>  [7] "alternative"           "audience"             
#>  [9] "available"             "bibliographicCitation"
#> [11] "conformsTo"            "contributor"          
#> [13] "coverage"              "created"              
#> [15] "creator"               "date"                 
#> [17] "dateAccepted"          "dateCopyrighted"      
#> [19] "dateSubmitted"         "description"

Future work

DwC-A files can be very large – This is for sure going to be a pain point for some.
We'll continue to test and refine on big data files.

Feedback?

We'd love to know what people think about this package.

Documentation can be better, e.g., there's no vignette yet (but adding
that soon).

To leave a comment for the author, please follow the link and comment on their blog: rOpenSci Blog - R.

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