# NOT RUN {
(key <- name_backbone(name='Encelia californica')$speciesKey)
occ_data(taxonKey = key, limit = 4)
(res <- occ_data(taxonKey = key, limit = 400))
# Return 20 results, this is the default by the way
(key <- name_suggest(q='Helianthus annuus', rank='species')$key[1])
occ_data(taxonKey=key, limit=20)
# Instead of getting a taxon key first, you can search for a name directly
## However, note that using this approach (with \code{scientificName="..."})
## you are getting synonyms too. The results for using \code{scientifcName}
## and \code{taxonKey} parameters are the same in this case, but I wouldn't
## be surprised if for some names they return different results
occ_data(scientificName = 'Ursus americanus', curlopts=list(verbose=TRUE))
key <- name_backbone(name = 'Ursus americanus', rank='species')$usageKey
occ_data(taxonKey = key)
# Search by dataset key
occ_data(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a', limit=10)
# Search by catalog number
occ_data(catalogNumber="49366", limit=10)
## separate requests: use a vector of strings
occ_data(catalogNumber=c("49366","Bird.27847588"), limit=10)
## one request, many instances of same parameter: use semi-colon sep. string
occ_data(catalogNumber="49366;Bird.27847588", limit=10)
# Use paging parameters (limit and start) to page. Note the different results
# for the two queries below.
occ_data(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a',start=10,limit=5)
occ_data(datasetKey='7b5d6a48-f762-11e1-a439-00145eb45e9a',start=20,limit=5)
# Many dataset keys
## separate requests: use a vector of strings
occ_data(datasetKey=c("50c9509d-22c7-4a22-a47d-8c48425ef4a7",
"7b5d6a48-f762-11e1-a439-00145eb45e9a"), limit=20)
## one request, many instances of same parameter: use semi-colon sep. string
v="50c9509d-22c7-4a22-a47d-8c48425ef4a7;7b5d6a48-f762-11e1-a439-00145eb45e9a"
occ_data(datasetKey = v, limit=20)
# Search by recorder
occ_data(recordedBy="smith", limit=20)
# Many collector names
## separate requests: use a vector of strings
occ_data(recordedBy=c("smith","BJ Stacey"), limit=10)
## one request, many instances of same parameter: use semi-colon sep. string
occ_data(recordedBy="smith;BJ Stacey", limit=10)
# Pass in curl options for extra fun
occ_data(taxonKey=2433407, limit=20, curlopts=list(verbose=TRUE))
occ_data(taxonKey=2433407, limit=20,
curlopts = list(
noprogress = FALSE,
progressfunction = function(down, up) {
cat(sprintf("up: %d | down %d\n", up, down))
return(TRUE)
}
)
)
# occ_data(taxonKey=2433407, limit=20, curlopts=list(timeout_ms=1))
# Search for many species
splist <- c('Cyanocitta stelleri', 'Junco hyemalis', 'Aix sponsa')
keys <- sapply(splist, function(x) name_suggest(x)$key[1], USE.NAMES=FALSE)
## separate requests: use a vector of strings
occ_data(taxonKey = keys, limit=5)
## one request, many instances of same parameter: use semi-colon sep. string
occ_data(taxonKey = paste0(keys, collapse = ";"), limit=5)
# Search using a synonym name
# Note that you'll see a message printing out that the accepted name will
# be used
occ_data(scientificName = 'Pulsatilla patens', limit=5)
# Search on latitidue and longitude
occ_data(decimalLatitude=40, decimalLongitude=-120, limit = 10)
# Search on a bounding box
## in well known text format
### polygon
occ_data(geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))',
limit=20)
### multipolygon
wkt <- 'MULTIPOLYGON(((-123 38, -123 43, -116 43, -116 38, -123 38)),
((-97 41, -97 45, -93 45, -93 41, -97 41)))'
occ_data(geometry = gsub("\n\\s+", "", wkt), limit = 20)
### polygon and taxonkey
key <- name_suggest(q='Aesculus hippocastanum')$key[1]
occ_data(taxonKey=key,
geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))',
limit=20)
## or using bounding box, converted to WKT internally
occ_data(geometry=c(-125.0,38.4,-121.8,40.9), limit=20)
## you can seaerch on many geometry objects
### separate requests: use a vector of strings
wkts <-
c('POLYGON((-102.2 46.0,-93.9 46.0,-93.9 43.7,-102.2 43.7,-102.2 46.0))',
'POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))')
occ_data(geometry = wkts, limit=20)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(geometry = paste0(wkts, collapse = ";"), limit=20)
# Search on a long WKT string - too long for a GBIF search API request
## By default, a very long WKT string will likely cause a request failure as
## GBIF only handles strings up to about 1500 characters long. You can leave as is, or
## - Alternatively, you can choose to break up your polygon into many, and do a
## data request on each piece, and the output is put back together (see below)
## - Or, 2nd alternatively, you could use the GBIF download API
wkt <- "POLYGON((13.26349675655365 52.53991761181831,18.36115300655365 54.11445544219924,
21.87677800655365 53.80418956368524,24.68927800655365 54.217364774722455,28.20490300655365
54.320018299365124,30.49005925655365 52.85948216284084,34.70880925655365 52.753220564427814,
35.93927800655365 50.46131871049754,39.63068425655365 49.55761261299145,40.86115300655365
46.381388009130845,34.00568425655365 45.279102926537,33.30255925655365 48.636868465271846,
30.13849675655365 49.78513301801265,28.38068425655365 47.2236377039631,29.78693425655365
44.6572866068524,27.67755925655365 42.62220075124676,23.10724675655365 43.77542058000212,
24.51349675655365 47.10412345120368,26.79865300655365 49.55761261299145,23.98615300655365
52.00209943876426,23.63459050655365 49.44345313705238,19.41584050655365 47.580567827212114,
19.59162175655365 44.90682206053508,20.11896550655365 42.36297154876359,22.93146550655365
40.651849782081555,25.56818425655365 39.98171166226459,29.61115300655365 40.78507856230178,
32.95099675655365 40.38459278067577,32.95099675655365 37.37491910393631,26.27130925655365
33.65619609886799,22.05255925655365 36.814081996401605,18.71271550655365 36.1072176729021,
18.53693425655365 39.16878677351903,15.37287175655365 38.346355762190846,15.19709050655365
41.578843777436326,12.56037175655365 41.050735748143424,12.56037175655365 44.02872991212046,
15.19709050655365 45.52594200494078,16.42755925655365 48.05271546733352,17.48224675655365
48.86865641518059,10.62677800655365 47.817178329053135,9.57209050655365 44.154980365192,
8.16584050655365 40.51835445724746,6.05646550655365 36.53210972067291,0.9588092565536499
31.583640057148145,-5.54509699344635 35.68001485298146,-6.77556574344635 40.51835445724746,
-9.41228449344635 38.346355762190846,-12.40056574344635 35.10683619158607,-15.74040949344635
38.07010978950028,-14.68572199344635 41.31532459432774,-11.69744074344635 43.64836179231387,
-8.88494074344635 42.88035509418534,-4.31462824344635 43.52103366008421,-8.35759699344635
47.2236377039631,-8.18181574344635 50.12441989397795,-5.01775324344635 49.55761261299145,
-2.73259699344635 46.25998980446569,-1.67790949344635 44.154980365192,-1.32634699344635
39.30493590580802,2.18927800655365 41.44721797271696,4.47443425655365 43.26556960420879,
2.18927800655365 46.7439668697322,1.83771550655365 50.3492841273576,6.93537175655365
49.671505849335254,5.00177800655365 52.32557322466785,7.81427800655365 51.67627099802223,
7.81427800655365 54.5245591562317,10.97834050655365 51.89375191441792,10.97834050655365
55.43241335888528,13.26349675655365 52.53991761181831))"
wkt <- gsub("\n", " ", wkt)
#### Default option with large WKT string fails
# res <- occ_data(geometry = wkt)
#### if WKT too long, with 'geom_big=bbox': makes into bounding box
res <- occ_data(geometry = wkt, geom_big = "bbox")
library("rgeos")
library("sp")
wktsp <- readWKT(wkt)
plot(wktsp)
coordinates(res$data) <- ~decimalLongitude+decimalLatitude
points(res$data)
#### Or, use 'geom_big=axe'
(res <- occ_data(geometry = wkt, geom_big = "axe"))
##### manipulate essentially number of polygons that result, so number of requests
###### default geom_size is 40
###### fewer calls
(res <- occ_data(geometry = wkt, geom_big = "axe", geom_size=50))
###### more calls
(res <- occ_data(geometry = wkt, geom_big = "axe", geom_size=30))
# Search on country
occ_data(country='US', limit=20)
isocodes[grep("France", isocodes$name),"code"]
occ_data(country='FR', limit=20)
occ_data(country='DE', limit=20)
### separate requests: use a vector of strings
occ_data(country=c('US','DE'), limit=20)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(country = 'US;DE', limit=20)
# Get only occurrences with lat/long data
occ_data(taxonKey=key, hasCoordinate=TRUE, limit=20)
# Get only occurrences that were recorded as living specimens
occ_data(basisOfRecord="LIVING_SPECIMEN", hasCoordinate=TRUE, limit=20)
# Get occurrences for a particular eventDate
occ_data(taxonKey=key, eventDate="2013", limit=20)
occ_data(taxonKey=key, year="2013", limit=20)
occ_data(taxonKey=key, month="6", limit=20)
# Get occurrences based on depth
key <- name_backbone(name='Salmo salar', kingdom='animals')$speciesKey
occ_data(taxonKey=key, depth=1, limit=20)
# Get occurrences based on elevation
key <- name_backbone(name='Puma concolor', kingdom='animals')$speciesKey
occ_data(taxonKey=key, elevation=50, hasCoordinate=TRUE, limit=20)
# Get occurrences based on institutionCode
occ_data(institutionCode="TLMF", limit=20)
### separate requests: use a vector of strings
occ_data(institutionCode=c("TLMF","ArtDatabanken"), limit=20)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(institutionCode = "TLMF;ArtDatabanken", limit=20)
# Get occurrences based on collectionCode
occ_data(collectionCode="Floristic Databases MV - Higher Plants", limit=20)
### separate requests: use a vector of strings
occ_data(collectionCode=c("Floristic Databases MV - Higher Plants",
"Artport"), limit = 20)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(collectionCode = "Floristic Databases MV - Higher Plants;Artport",
limit = 20)
# Get only those occurrences with spatial issues
occ_data(taxonKey=key, hasGeospatialIssue=TRUE, limit=20)
# Search using a query string
occ_data(search="kingfisher", limit=20)
## spell check - only works with the `search` parameter
### spelled correctly - same result as above call
occ_data(search = "kingfisher", limit=20, spellCheck = TRUE)
### spelled incorrectly - stops with suggested spelling
# occ_data(search = "kajsdkla", limit=20, spellCheck = TRUE)
### spelled incorrectly - stops with many suggested spellings
### and number of results for each
# occ_data(search = "helir", limit=20, spellCheck = TRUE)
# search on repatriated - doesn't work right now
# occ_data(repatriated = "")
# search on phylumKey
occ_data(phylumKey = 7707728, limit = 5)
# search on kingdomKey
occ_data(kingdomKey = 1, limit = 5)
# search on classKey
occ_data(classKey = 216, limit = 5)
# search on orderKey
occ_data(orderKey = 7192402, limit = 5)
# search on familyKey
occ_data(familyKey = 3925, limit = 5)
# search on genusKey
occ_data(genusKey = 1935496, limit = 5)
# search on establishmentMeans
occ_data(establishmentMeans = "INVASIVE", limit = 5)
occ_data(establishmentMeans = "NATIVE", limit = 5)
occ_data(establishmentMeans = "UNCERTAIN", limit = 5)
### separate requests: use a vector of strings
occ_data(establishmentMeans = c("INVASIVE", "NATIVE"), limit = 5)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(establishmentMeans = "INVASIVE;NATIVE", limit = 5)
# search on protocol
occ_data(protocol = "DIGIR", limit = 5)
# search on license
occ_data(license = "CC_BY_4_0", limit = 5)
# search on organismId
occ_data(organismId = "100", limit = 5)
# search on publishingOrg
occ_data(publishingOrg = "28eb1a3f-1c15-4a95-931a-4af90ecb574d", limit = 5)
# search on stateProvince
occ_data(stateProvince = "California", limit = 5)
# search on waterBody
occ_data(waterBody = "pacific ocean", limit = 5)
# search on locality
occ_data(locality = "Trondheim", limit = 5)
### separate requests: use a vector of strings
res <- occ_data(locality = c("Trondheim", "Hovekilen"), limit = 5)
res$Trondheim$data
res$Hovekilen$data
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(locality = "Trondheim;Hovekilen", limit = 5)
# Range queries
## See Detail for parameters that support range queries
occ_data(depth='50,100', limit = 20)
### this is not a range search, but does two searches for each depth
occ_data(depth=c(50,100), limit = 20)
## Range search with year
occ_data(year='1999,2000', limit=20)
## Range search with latitude
occ_data(decimalLatitude='29.59,29.6', limit = 20)
# Search by specimen type status
## Look for possible values of the typeStatus parameter looking at the typestatus dataset
occ_data(typeStatus = 'allotype', limit = 20)$data[,c('name','typeStatus')]
# Search by specimen record number
## This is the record number of the person/group that submitted the data, not GBIF's numbers
## You can see that many different groups have record number 1, so not super helpful
occ_data(recordNumber = 1, limit = 20)$data[,c('name','recordNumber','recordedBy')]
# Search by last time interpreted: Date the record was last modified in GBIF
## The lastInterpreted parameter accepts ISO 8601 format dates, including
## yyyy, yyyy-MM, yyyy-MM-dd, or MM-dd. Range queries are accepted for lastInterpreted
occ_data(lastInterpreted = '2016-04-02', limit = 20)
# Search for occurrences with images
occ_data(mediaType = 'StillImage', limit = 20)
occ_data(mediaType = 'MovingImage', limit = 20)
occ_data(mediaType = 'Sound', limit = 20)
# Search by continent
## One of africa, antarctica, asia, europe, north_america, oceania, or
## south_america
occ_data(continent = 'south_america', limit = 20)$meta
occ_data(continent = 'africa', limit = 20)$meta
occ_data(continent = 'oceania', limit = 20)$meta
occ_data(continent = 'antarctica', limit = 20)$meta
### separate requests: use a vector of strings
occ_data(continent = c('south_america', 'oceania'), limit = 20)
### one request, many instances of same parameter: use semi-colon sep. string
occ_data(continent = 'south_america;oceania', limit = 20)
# Query based on issues - see Details for options
## one issue
x <- occ_data(taxonKey=1, issue='DEPTH_UNLIKELY', limit = 20)
x$data[,c('name','key','decimalLatitude','decimalLongitude','depth')]
## two issues
occ_data(taxonKey=1, issue=c('DEPTH_UNLIKELY','COORDINATE_ROUNDED'), limit = 20)
# Show all records in the Arizona State Lichen Collection that cant be matched to the GBIF
# backbone properly:
occ_data(datasetKey='84c0e1a0-f762-11e1-a439-00145eb45e9a',
issue=c('TAXON_MATCH_NONE','TAXON_MATCH_HIGHERRANK'), limit = 20)
# Parsing output by issue
(res <- occ_data(geometry='POLYGON((30.1 10.1, 10 20, 20 40, 40 40, 30.1 10.1))', limit = 50))
## what do issues mean, can print whole table, or search for matches
head(gbif_issues())
gbif_issues()[ gbif_issues()$code %in% c('cdround','cudc','gass84','txmathi'), ]
## or parse issues in various ways
### remove data rows with certain issue classes
library('magrittr')
res %>% occ_issues(gass84)
### split issues into separate columns
res %>% occ_issues(mutate = "split")
### expand issues to more descriptive names
res %>% occ_issues(mutate = "expand")
### split and expand
res %>% occ_issues(mutate = "split_expand")
### split, expand, and remove an issue class
res %>% occ_issues(-cudc, mutate = "split_expand")
# }
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