Installation
The easiest way to get rminka is to install from github
repository:
devtools::install_github("Development-BioMarine/rminkav3")Quickstart guide
Get observations
get_minka_obs() This function retrieves observations
from Minka. The text or taxon search can be refined by observation date,
record quality and location.
It is recommended to set the
qualityargument to"research"in order to get more reliable data that has been validated by several contributors.
Fuzzy search
You can search for observations by either common or scientific name. It will search the entire database, so the search below will return entries that mention seabream fishes , not just seabream observations.
sard <- get_minka_obs(query = "seabream", year = 2021)
unique(sard$scientific_name)
#> [1] "Lithognathus mormyrus" "Sparidae"
#> [3] "Diplodus sargus" "Diplodus annularis"
#> [5] "Diplodus vulgaris" "Oblada melanura"
#> [7] "Diplodus puntazzo" "Sparus aurata"
#> [9] "Pagellus bogaraveo" "Diplodus cadenati"
#> [11] "Pagellus acarne" "Spondyliosoma cantharus"
#> [13] "Pagrus caeruleostictus" "Pagrus auriga"Note that
get_minka_obs()will return 500 observations by default. This can be controlled with themaxresultsargument.
sard_max_results <- get_minka_obs(query = "seabream", year = 2021, maxresults = 10)
sard_max_results[,1:6]
#> scientific_name datetime description
#> 1 Lithognathus mormyrus 2021-10-03 11:55:00 +0200
#> 2 Sparidae 2021-10-03 11:55:00 +0200
#> 3 Diplodus sargus 2021-08-05 13:23:00 +0200
#> 4 Diplodus annularis 2021-08-04 11:19:00 +0200
#> 5 Diplodus sargus 2021-08-03 15:19:00 +0200
#> 6 Diplodus vulgaris 2021-08-03 15:19:00 +0200
#> 7 Oblada melanura 2021-08-03 15:13:00 +0200
#> 8 Diplodus vulgaris 2021-07-28 08:51:00 +0200
#> 9 Oblada melanura 2021-07-25 12:10:00 +0200
#> 10 Diplodus sargus 2021-07-04 09:52:00 +0200
#> place_guess latitude longitude
#> 1 Barcelona, España 41.26480 2.005203
#> 2 Barcelona, España 41.26480 2.005200
#> 3 Spain 40.05483 3.883954
#> 4 Spain 39.95923 4.265633
#> 5 39.93600 3.937817
#> 6 39.93600 3.937833
#> 7 39.93646 3.938442
#> 8 41.08978 1.228733
#> 9 41.08981 1.228671
#> 10 41.08979 1.228717Taxon search
To return only records of a specific species or taxonomic group, use
the taxon_name argument. For example, to return
observations of anything from the family Sparidae, and restricting the
search to the year 2022:
sparidae <- get_minka_obs(taxon_name = "Sparidae", year = 2022)
# how many unique taxa?
length(unique(sparidae$scientific_name))
#> [1] 20
#The species are:
unique(sparidae$scientific_name)
#> [1] "Pagrus pagrus" "Diplodus cervinus"
#> [3] "Diplodus vulgaris" "Oblada melanura"
#> [5] "Diplodus puntazzo" "Diplodus sargus"
#> [7] "Sparus aurata" "Lithognathus mormyrus"
#> [9] "Sarpa salpa" "Boops boops"
#> [11] "Dentex dentex" "Pagellus acarne"
#> [13] "Pagellus erythrinus" "Dentex gibbosus"
#> [15] "Spondyliosoma cantharus" "Sparidae"
#> [17] "Pagrus auriga" "Diplodus annularis"
#> [19] "Diplodus" "Diplodus cadenati"And to return only the seabream fish observations that also mention the term “banc”:
sard_banc <- get_minka_obs(taxon_name = "Diplodus", query = "banc")
count_sard <- nrow(sard_banc)
count_sard
#> [1] 4
#the observarions are
sard_banc[1:count_sard,1:2]
#> scientific_name datetime
#> 1 Diplodus vulgaris 2018-07-26 00:00:00 +0100
#> 2 Diplodus vulgaris 2018-07-26 00:00:00 +0100
#> 3 Diplodus vulgaris 2018-07-04 00:00:00 +0100
#> 4 Diplodus vulgaris 2019-07-21 00:00:00 +0100Bounding box search
You can also search within a bounding box by giving a simple set of coordinates. The set of coordinates are defined by c( min Long, min Lat, max Long, max Lat)
bounds_forum <- c(41.407281, 2.224977, 41.409892, 2.228652 )
diplodus_forum <- get_minka_obs(query = "Diplodus sargus", bounds = bounds_forum, year = 2024, month = 5, maxresults = 7)
diplodus_forum[1,1:6]
#> scientific_name datetime description place_guess latitude
#> 1 Diplodus sargus 2024-05-18 11:40:00 +0200 NA Forum 41.40921
#> longitude
#> 1 2.227122and the representation using leaflet is:
leaflet() %>%
addTiles() %>%
setView(lng = 2.226725, lat = 41.408492, zoom = 16.35) %>%
addRectangles(lng1 = 2.224977, lat1 = 41.407281,
lng2 = 2.228652, lat2 = 41.409892) %>%
addMarkers (
lng = diplodus_forum$longitude,
lat = diplodus_forum$latitude,
label = paste('Id =', as.character(diplodus_forum$id))
)Leaflet map with the observations
Other functions
Get information and observations by project
You can get all the observations for a project if you know its ID or name as an Minka slug.
## Just get info about a project
urbamar <- get_minka_obs_project("urbamarbio", type = "info", raw = FALSE)
urbamar$project_observations_count
#> [1] 55948
## Now get all the observations for that project
urbamar_obs <- get_minka_obs_project("biodiversitat-marina-de-les-platges-de-sant-adria-del-besos", type = "observations")
#> Getting records 0-200
#> Getting records up to 400
#> Getting records up to 600
#> Getting records up to 800
#> Getting records up to 1000
#> Getting records up to 1200
#> Done.
#Geting the first 5 observations
urbamar_obs[1:5,8:1]
#> species_guess timeframe map_scale longitude latitude
#> 1 Rabosa groga NA NA 2.2384089231 41.4250151953
#> 2 Bavosa de plomall NA NA 2.2384089231 41.4250151953
#> 3 Morruda NA NA 2.2384089231 41.4250151953
#> 4 Limaria tuberculata NA NA 2.2384089231 41.4250151953
#> 5 Variada NA NA 2.2384089231 41.4250151953
#> description observed_on id
#> 1 <NA> 2024-09-10 354734
#> 2 <NA> 2024-09-10 354735
#> 3 <NA> 2024-09-10 354736
#> 4 <NA> 2024-09-10 354737
#> 5 <NA> 2024-09-10 354738Get observation details
Detailed information about a specific observation can be retrieved by observation ID. The easiest way to get the ID is from a previous search for that taxon.
ident <- sard_banc$id[1]
ident
#> [1] 80229
#get_minka_obs_id(ident)[1:4,1:5]Get all observations by user
If you just want all the observations by a user you can download all their observations by user ID. A word of warning though, this can be quite large (easily into the 1000’s).
user_obs <- get_minka_obs_user('ramonservitje')
(user_obs)[1:5,1:3]
#> scientific_name datetime description
#> 1 Porphyrio porphyrio 2024-11-10 12:03:00 +0100
#> 2 Podiceps cristatus 2024-11-10 13:21:00 +0100
#> 3 Circus aeruginosus 2024-11-10 13:32:00 +0100
#> 4 Podiceps nigricollis 2024-11-10 13:48:00 +0100
#> 5 Pelophylax perezi 2024-11-09 12:10:00 +0100
#it is possible to view the images with the links in Minka
url <- user_obs$image_url[412]
# Read the image
image <- image_read(url)
# Show the image
print(image)
#> # A tibble: 1 × 7
#> format width height colorspace matte filesize density
#> <chr> <int> <int> <chr> <lgl> <int> <chr>
#> 1 JPEG 500 397 sRGB FALSE 173509 72x72
Picture of an user observation