SHARK
SHARK is the Swedish Ocean Archive’s platform for data downloads. It
stores biological, physical, and chemical marine environmental
monitoring data. On behalf of the Swedish Agency for Marine and Water
Management, SMHI serves as the national data host for oceanography and
marine biology and is designated by UNESCO as a National Oceanographic
Data Center (NODC). The data can be accessed via a web interface or through the API, as demonstrated in this
tutorial using SHARK4R.
Retrieve Data Table
Data can be retrieved with the same filtering options available in SHARK. To see the available filtering
options, please refer to get_shark_options() and the
information below.
# Retrieve chlorophyll data for April to June from 2019 to 2020
shark_data <- get_shark_data(fromYear = 2019,
toYear = 2020,
months = c(4, 5, 6),
dataTypes = c("Chlorophyll"),
verbose = FALSE)
# Print data
print(shark_data)## # A tibble: 179 × 72
## delivery_datatype check_status_sv data_checked_by_sv visit_year visit_month
## <chr> <chr> <chr> <dbl> <dbl>
## 1 Chlorophyll Klar Leverantör 2020 6
## 2 Chlorophyll Klar Leverantör 2020 6
## 3 Chlorophyll Klar Leverantör 2020 6
## 4 Chlorophyll Klar Leverantör 2020 6
## 5 Chlorophyll Klar Leverantör 2020 6
## 6 Chlorophyll Klar Leverantör 2020 6
## 7 Chlorophyll Klar Leverantör 2020 6
## 8 Chlorophyll Klar Leverantör 2020 6
## 9 Chlorophyll Klar Leverantör 2020 6
## 10 Chlorophyll Klar Leverantör 2020 6
## # ℹ 169 more rows
## # ℹ 67 more variables: station_name <chr>, reported_station_name <chr>,
## # sample_location_id <dbl>, station_id <dbl>, sample_project_name_sv <lgl>,
## # sample_orderer_name_sv <lgl>, visit_id <dbl>, visit_date <lgl>,
## # shark_sample_id_md5 <chr>, sample_date <date>, sample_time <time>,
## # sample_enddate <lgl>, sample_endtime <lgl>, sample_latitude_dm <chr>,
## # sample_longitude_dm <chr>, sample_latitude_dd <dbl>, …Get SHARK API Options
Filtering options, including data types, dataset names, stations,
taxa, and more, can be retrieved using the
get_shark_options() function.
# Retrieve available search options
shark_options <- get_shark_options()
# List the names of the available options
names(shark_options)## [1] "datasets" "dataTypes" "parameters"
## [4] "minYear" "maxYear" "months"
## [7] "checkStatuses" "qualityFlags" "deliverers"
## [10] "orderers" "projects" "redListedCategories"
## [13] "taxa" "stations" "seaAreas"
## [16] "vattenDistrikt" "typOmraden" "seaBasins"
## [19] "counties" "municipalities" "waterCategories"
## [22] "helcomOspar" "parametersForDatatype" "headerlangers"
## [25] "minYearPerDatatype"
# View available datatypes
dataTypes <- shark_options$dataTypes
print(dataTypes)## [1] "Bacterioplankton" "Chlorophyll" "Epibenthos"
## [4] "Grey seal" "Harbour Porpoise" "Harbour seal"
## [7] "Physical and Chemical" "Phytoplankton" "Picoplankton"
## [10] "Plankton Barcoding" "Plankton Imaging" "Primary production"
## [13] "Profile" "Ringed seal" "Seal pathology"
## [16] "Sedimentation" "Zoobenthos" "Zooplankton"
# View available dataset names
datasetNames <- shark_options$datasets
head(datasetNames) # Print first few dataset names## [1] "SHARK_Bacterioplankton_ABUND_2023_UMSC_version_2024-06-04.zip"
## [2] "SHARK_Bacterioplankton_ABU_2006_UMSC_Bactabund_version_2024-09-27.zip"
## [3] "SHARK_Bacterioplankton_ABU_2007_UMSC_Bactabund_version_2024-09-27.zip"
## [4] "SHARK_Bacterioplankton_ABU_2008_UMSC_Bactabund_version_2024-09-27.zip"
## [5] "SHARK_Bacterioplankton_ABU_2009_UMSC_Bactabund_version_2024-09-27.zip"
## [6] "SHARK_Bacterioplankton_ABU_2010_UMSC_Bactabund_version_2024-09-27.zip"Retrieve Datasets (Zip-archives)
In addition to accessing data in tabular form, you can also download complete datasets packaged as zip archives. This is useful if you want to store complete datasets locally for further analysis.
To explore all available dataset names, use the
get_shark_options(). Once you know which datasets you need,
you can pass their names (or partial names) to the
get_shark_datasets() function.
# Select a dataset name (e.g., the first two in the list)
dataset_name <- datasetNames[1:2]
# Download the dataset as a zip-archive to a temporary directory
shark_data_zip <- get_shark_datasets(dataset_name,
save_dir = tempdir(),
verbose = FALSE) # Quiet output
# Print the paths to the downloaded files
print(shark_data_zip)## $`SHARK_Bacterioplankton_ABUND_2023_UMSC_version_2024-06-04.zip`
## [1] "/tmp/RtmpkyGC3i/SHARK_Bacterioplankton_ABUND_2023_UMSC_version_2024-06-04.zip"
##
## $`SHARK_Bacterioplankton_ABU_2006_UMSC_Bactabund_version_2024-09-27.zip`
## [1] "/tmp/RtmpkyGC3i/SHARK_Bacterioplankton_ABU_2006_UMSC_Bactabund_version_2024-09-27.zip"Please note that SHARK4R also includes several useful
functions for reading local SHARK data files, such as
shark_read(), shark_read_zip(),
shark_read_deliv() and
shark_read_deliv_xls().
Citation
## To cite package 'SHARK4R' in publications use:
##
## Markus Lindh, Anders Torstensson (2025). SHARK4R: Retrieving,
## Analyzing, and Validating Marine Data from SHARK and Nordic
## Microalgae. R package version 0.1.7.9000.
## https://doi.org/10.5281/zenodo.14169399
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
## title = {SHARK4R: Retrieving, Analyzing, and Validating Marine Data from SHARK and Nordic Microalgae},
## author = {Markus Lindh and Anders Torstensson},
## year = {2025},
## note = {R package version 0.1.7.9000},
## url = {https://doi.org/10.5281/zenodo.14169399},
## }