Nothing
Download data
In galah: Biodiversity Data from the GBIF Node Network
The atlas_ functions are used to return data from the atlas chosen using
galah_config(). They are:
atlas_countsatlas_occurrencesatlas_speciesatlas_mediaatlas_taxonomy
The final atlas_ function - atlas_citation - is unusual in that it does not
return any new data. Instead it provides a citation for an existing dataset (
downloaded using atlas_occurrences) that has an associated DOI. The other
functions are described below.
Record counts
atlas_counts() provides summary counts on records in the specified atlas,
without needing to download all the records.
galah_config(atlas = "Australia")
# Total number of records in the ALA
atlas_counts()
## # A tibble: 1 × 1
## count
## <int>
## 1 131963195
In addition to the filter arguments, it has an optional group_by argument,
which provides counts binned by the requested field.
galah_call() |>
galah_group_by(kingdom) |>
atlas_counts()
## # A tibble: 11 × 2
## kingdom count
## <chr> <int>
## 1 Animalia 101176164
## 2 Plantae 26026027
## 3 Fungi 2285235
## 4 Chromista 1020325
## 5 Protista 352282
## 6 Bacteria 113165
## 7 Eukaryota 8821
## 8 Protozoa 4716
## 9 Archaea 4120
## 10 Virus 2306
## 11 Viroid 103
Species lists
A common use case of atlas data is to identify which species occur in a specified
region, time period, or taxonomic group. atlas_species() is similar to
search_taxa, in that it returns taxonomic information and unique identifiers
in a tibble. It differs in not being able to return information on taxonomic
levels other than the species; but also in being more flexible by supporting filtering:
species <- galah_call() |>
galah_identify("Rodentia") |>
galah_filter(stateProvince == "Northern Territory") |>
atlas_species()
species |> head()
## # A tibble: 6 × 10
## kingdom phylum class order family genus species author species_guid vernacular_name
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 Animalia Chordata Mammalia Roden… Murid… Pseu… Pseudo… (Goul… https://bio… Delicate Mouse
## 2 Animalia Chordata Mammalia Roden… Murid… Mese… Mesemb… (J.E.… https://bio… Black-footed T…
## 3 Animalia Chordata Mammalia Roden… Murid… Zyzo… Zyzomy… (Thom… https://bio… Common Rock-rat
## 4 Animalia Chordata Mammalia Roden… Murid… Pseu… Pseudo… (Wait… https://bio… Sandy Inland M…
## 5 Animalia Chordata Mammalia Roden… Murid… Melo… Melomy… (Rams… https://bio… Grassland Melo…
## 6 Animalia Chordata Mammalia Roden… Murid… Noto… Notomy… Thoma… https://bio… Spinifex Hoppi…
Occurrence data
To download occurrence data you will need to specify your email in
galah_config(). This email must be associated with an active ALA account. See
more information in the config section
galah_config(email = "your_email@email.com", atlas = "Australia")
Download occurrence records for Eolophus roseicapilla
occ <- galah_call() |>
galah_identify("Eolophus roseicapilla") |>
galah_filter(
stateProvince == "Australian Capital Territory",
year >= 2010,
profile = "ALA"
) |>
galah_select(institutionID, group = "basic") |>
atlas_occurrences()
## Retrying in 1 seconds.
## Retrying in 2 seconds.
## Retrying in 4 seconds.
occ |> head()
## # A tibble: 6 × 9
## recordID scientificName taxonConceptID decimalLatitude decimalLongitude
## <chr> <chr> <chr> <dbl> <dbl>
## 1 0000a928-d756-42eb-8058-6f… Eolophus rose… https://biodi… -35.6 149.
## 2 0001bc78-d2e9-48aa-8b9d-d6… Eolophus rose… https://biodi… -35.2 149.
## 3 0002064f-08ea-425b-97c5-26… Eolophus rose… https://biodi… -35.3 149.
## 4 00022dd2-9f85-4802-b837-7f… Eolophus rose… https://biodi… -35.3 149.
## 5 0002cc35-8d5a-4d20-8012-12… Eolophus rose… https://biodi… -35.3 149.
## 6 00030a8c-082f-44f0-898a-ad… Eolophus rose… https://biodi… -35.3 149.
## # ℹ 4 more variables: eventDate <dttm>, occurrenceStatus <chr>, dataResourceName <chr>,
## # institutionID <lgl>
Media metadata
In addition to text data describing individual occurrences and their attributes,
ALA stores images, sounds and videos associated with a given record. Metadata on
these records can be downloaded to R using atlas_media() and the same set of
filters as the other data download functions.
media_data <- galah_call() |>
galah_identify("Eolophus roseicapilla") |>
galah_filter(
year == 2020,
cl22 == "Australian Capital Territory") |>
atlas_media()
## Retrying in 1 seconds.
media_data |> head()
## # A tibble: 6 × 19
## media_id recordID scientificName taxonConceptID decimalLatitude decimalLongitude
## <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 ff8322d0-f44c-47a… 003a192… Eolophus rose… https://biodi… -35.3 149.
## 2 c66fc819-7022-44f… 015ee7c… Eolophus rose… https://biodi… -35.4 149.
## 3 fe6d7b94-9e61-4ac… 05e86b7… Eolophus rose… https://biodi… -35.4 149.
## 4 2f4d32c0-a084-4bb… 063bb0f… Eolophus rose… https://biodi… -35.6 149.
## 5 73407414-0707-429… 063bb0f… Eolophus rose… https://biodi… -35.6 149.
## 6 89171c49-5a64-423… 063bb0f… Eolophus rose… https://biodi… -35.6 149.
## # ℹ 13 more variables: eventDate <dttm>, occurrenceStatus <chr>, dataResourceName <chr>,
## # multimedia <chr>, images <chr>, videos <lgl>, sounds <lgl>, creator <chr>,
## # license <chr>, mimetype <chr>, width <int>, height <int>, image_url <chr>
To actually download the media files to your computer, use [collect_media()].
Taxonomic trees
atlas_taxonomy provides a way to build taxonomic trees from one clade down to
another using each service's internal taxonomy. Specify which taxonomic level
your tree will go down to with galah_filter() using the rank argument.
galah_call() |>
galah_identify("chordata") |>
galah_filter(rank == class) |>
atlas_taxonomy()
## # A tibble: 19 × 4
## name rank parent_taxon_concept_id taxon_concept_id
## <chr> <chr> <chr> <chr>
## 1 Chordata phylum <NA> https://biodive…
## 2 Cephalochordata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive…
## 3 Tunicata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive…
## 4 Appendicularia class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive…
## 5 Ascidiacea class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive…
## 6 Thaliacea class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive…
## 7 Vertebrata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive…
## 8 Agnatha informal https://biodiversity.org.au/afd/taxa/5d6076b1… https://biodive…
## 9 Myxini informal https://biodiversity.org.au/afd/taxa/66db22c8… https://biodive…
## 10 Petromyzontida informal https://biodiversity.org.au/afd/taxa/66db22c8… https://biodive…
## 11 Gnathostomata informal https://biodiversity.org.au/afd/taxa/5d6076b1… https://biodive…
## 12 Amphibia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
## 13 Aves class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
## 14 Mammalia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
## 15 Pisces informal https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
## 16 Actinopterygii class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive…
## 17 Chondrichthyes class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive…
## 18 Sarcopterygii class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive…
## 19 Reptilia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
Configuring galah
Various aspects of the galah package can be customized.
Email
To download occurrence records, you will need to provide an email address
registered with the service that you want to use (e.g. for the ALA you can
create an account
here).
Once an email is registered, it should be stored in the config:
galah_config(email = "myemail@gmail.com")
Setting your directory
By default, galah stores downloads in a temporary folder, meaning that the
local files are automatically deleted when the R session is ended. This
behaviour can be altered so that downloaded files are preserved by setting the
directory to a non-temporary location.
galah_config(directory = "example/dir")
Setting the download reason
ALA requires that you provide a reason when downloading occurrence data
(via the galah atlas_occurrences() function). The reason is set as
"scientific research" by default, but you can change this using galah_config().
See show_all_reasons() for valid download reasons.
galah_config(download_reason_id = your_reason_id)
Debugging
If things aren't working as expected, more detail (particularly about web
requests and caching behaviour) can be obtained by setting the verbose
configuration option:
galah_config(verbose = TRUE)
Try the galah package in your browser
Any scripts or data that you put into this service are public.
galah documentation built on Nov. 20, 2023, 9:07 a.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
The atlas_ functions are used to return data from the atlas chosen using
galah_config(). They are:
atlas_countsatlas_occurrencesatlas_speciesatlas_mediaatlas_taxonomy
The final atlas_ function - atlas_citation - is unusual in that it does not
return any new data. Instead it provides a citation for an existing dataset (
downloaded using atlas_occurrences) that has an associated DOI. The other
functions are described below.
Record counts
atlas_counts() provides summary counts on records in the specified atlas,
without needing to download all the records.
galah_config(atlas = "Australia") # Total number of records in the ALA atlas_counts()
## # A tibble: 1 × 1 ## count ## <int> ## 1 131963195
In addition to the filter arguments, it has an optional group_by argument,
which provides counts binned by the requested field.
galah_call() |> galah_group_by(kingdom) |> atlas_counts()
## # A tibble: 11 × 2 ## kingdom count ## <chr> <int> ## 1 Animalia 101176164 ## 2 Plantae 26026027 ## 3 Fungi 2285235 ## 4 Chromista 1020325 ## 5 Protista 352282 ## 6 Bacteria 113165 ## 7 Eukaryota 8821 ## 8 Protozoa 4716 ## 9 Archaea 4120 ## 10 Virus 2306 ## 11 Viroid 103
Species lists
A common use case of atlas data is to identify which species occur in a specified
region, time period, or taxonomic group. atlas_species() is similar to
search_taxa, in that it returns taxonomic information and unique identifiers
in a tibble. It differs in not being able to return information on taxonomic
levels other than the species; but also in being more flexible by supporting filtering:
species <- galah_call() |> galah_identify("Rodentia") |> galah_filter(stateProvince == "Northern Territory") |> atlas_species() species |> head()
## # A tibble: 6 × 10 ## kingdom phylum class order family genus species author species_guid vernacular_name ## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> ## 1 Animalia Chordata Mammalia Roden… Murid… Pseu… Pseudo… (Goul… https://bio… Delicate Mouse ## 2 Animalia Chordata Mammalia Roden… Murid… Mese… Mesemb… (J.E.… https://bio… Black-footed T… ## 3 Animalia Chordata Mammalia Roden… Murid… Zyzo… Zyzomy… (Thom… https://bio… Common Rock-rat ## 4 Animalia Chordata Mammalia Roden… Murid… Pseu… Pseudo… (Wait… https://bio… Sandy Inland M… ## 5 Animalia Chordata Mammalia Roden… Murid… Melo… Melomy… (Rams… https://bio… Grassland Melo… ## 6 Animalia Chordata Mammalia Roden… Murid… Noto… Notomy… Thoma… https://bio… Spinifex Hoppi…
Occurrence data
To download occurrence data you will need to specify your email in
galah_config(). This email must be associated with an active ALA account. See
more information in the config section
galah_config(email = "your_email@email.com", atlas = "Australia")
Download occurrence records for Eolophus roseicapilla
occ <- galah_call() |> galah_identify("Eolophus roseicapilla") |> galah_filter( stateProvince == "Australian Capital Territory", year >= 2010, profile = "ALA" ) |> galah_select(institutionID, group = "basic") |> atlas_occurrences()
## Retrying in 1 seconds. ## Retrying in 2 seconds. ## Retrying in 4 seconds.
occ |> head()
## # A tibble: 6 × 9 ## recordID scientificName taxonConceptID decimalLatitude decimalLongitude ## <chr> <chr> <chr> <dbl> <dbl> ## 1 0000a928-d756-42eb-8058-6f… Eolophus rose… https://biodi… -35.6 149. ## 2 0001bc78-d2e9-48aa-8b9d-d6… Eolophus rose… https://biodi… -35.2 149. ## 3 0002064f-08ea-425b-97c5-26… Eolophus rose… https://biodi… -35.3 149. ## 4 00022dd2-9f85-4802-b837-7f… Eolophus rose… https://biodi… -35.3 149. ## 5 0002cc35-8d5a-4d20-8012-12… Eolophus rose… https://biodi… -35.3 149. ## 6 00030a8c-082f-44f0-898a-ad… Eolophus rose… https://biodi… -35.3 149. ## # ℹ 4 more variables: eventDate <dttm>, occurrenceStatus <chr>, dataResourceName <chr>, ## # institutionID <lgl>
Media metadata
In addition to text data describing individual occurrences and their attributes,
ALA stores images, sounds and videos associated with a given record. Metadata on
these records can be downloaded to R using atlas_media() and the same set of
filters as the other data download functions.
media_data <- galah_call() |> galah_identify("Eolophus roseicapilla") |> galah_filter( year == 2020, cl22 == "Australian Capital Territory") |> atlas_media()
## Retrying in 1 seconds.
media_data |> head()
## # A tibble: 6 × 19 ## media_id recordID scientificName taxonConceptID decimalLatitude decimalLongitude ## <chr> <chr> <chr> <chr> <dbl> <dbl> ## 1 ff8322d0-f44c-47a… 003a192… Eolophus rose… https://biodi… -35.3 149. ## 2 c66fc819-7022-44f… 015ee7c… Eolophus rose… https://biodi… -35.4 149. ## 3 fe6d7b94-9e61-4ac… 05e86b7… Eolophus rose… https://biodi… -35.4 149. ## 4 2f4d32c0-a084-4bb… 063bb0f… Eolophus rose… https://biodi… -35.6 149. ## 5 73407414-0707-429… 063bb0f… Eolophus rose… https://biodi… -35.6 149. ## 6 89171c49-5a64-423… 063bb0f… Eolophus rose… https://biodi… -35.6 149. ## # ℹ 13 more variables: eventDate <dttm>, occurrenceStatus <chr>, dataResourceName <chr>, ## # multimedia <chr>, images <chr>, videos <lgl>, sounds <lgl>, creator <chr>, ## # license <chr>, mimetype <chr>, width <int>, height <int>, image_url <chr>
To actually download the media files to your computer, use [collect_media()].
Taxonomic trees
atlas_taxonomy provides a way to build taxonomic trees from one clade down to
another using each service's internal taxonomy. Specify which taxonomic level
your tree will go down to with galah_filter() using the rank argument.
galah_call() |> galah_identify("chordata") |> galah_filter(rank == class) |> atlas_taxonomy()
## # A tibble: 19 × 4 ## name rank parent_taxon_concept_id taxon_concept_id ## <chr> <chr> <chr> <chr> ## 1 Chordata phylum <NA> https://biodive… ## 2 Cephalochordata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive… ## 3 Tunicata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive… ## 4 Appendicularia class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive… ## 5 Ascidiacea class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive… ## 6 Thaliacea class https://biodiversity.org.au/afd/taxa/1c20ed62… https://biodive… ## 7 Vertebrata subphylum https://biodiversity.org.au/afd/taxa/065f1da4… https://biodive… ## 8 Agnatha informal https://biodiversity.org.au/afd/taxa/5d6076b1… https://biodive… ## 9 Myxini informal https://biodiversity.org.au/afd/taxa/66db22c8… https://biodive… ## 10 Petromyzontida informal https://biodiversity.org.au/afd/taxa/66db22c8… https://biodive… ## 11 Gnathostomata informal https://biodiversity.org.au/afd/taxa/5d6076b1… https://biodive… ## 12 Amphibia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive… ## 13 Aves class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive… ## 14 Mammalia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive… ## 15 Pisces informal https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive… ## 16 Actinopterygii class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive… ## 17 Chondrichthyes class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive… ## 18 Sarcopterygii class https://biodiversity.org.au/afd/taxa/e22efeb4… https://biodive… ## 19 Reptilia class https://biodiversity.org.au/afd/taxa/ef5515fd… https://biodive…
Configuring galah
Various aspects of the galah package can be customized.
To download occurrence records, you will need to provide an email address registered with the service that you want to use (e.g. for the ALA you can create an account here). Once an email is registered, it should be stored in the config:
galah_config(email = "myemail@gmail.com")
Setting your directory
By default, galah stores downloads in a temporary folder, meaning that the
local files are automatically deleted when the R session is ended. This
behaviour can be altered so that downloaded files are preserved by setting the
directory to a non-temporary location.
galah_config(directory = "example/dir")
Setting the download reason
ALA requires that you provide a reason when downloading occurrence data
(via the galah atlas_occurrences() function). The reason is set as
"scientific research" by default, but you can change this using galah_config().
See show_all_reasons() for valid download reasons.
galah_config(download_reason_id = your_reason_id)
Debugging
If things aren't working as expected, more detail (particularly about web
requests and caching behaviour) can be obtained by setting the verbose
configuration option:
galah_config(verbose = TRUE)
Try the galah package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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