pangaear is a data retrieval interface for the World Data Center PANGAEA (https://www.pangaea.de/). PANGAEA archieves published Earth & Environmental Science data under the following subjects: agriculture, atmosphere, biological classification, biosphere, chemistry, cryosphere, ecology, fisheries, geophysics, human dimensions, lakes & rives, land surface, lithosphere, oceans, and paleontology.
If you've not installed it yet, install from CRAN:
install.packages("pangaear")
Or the development version:
devtools::install_github("ropensci/pangaear")
library("pangaear")
pg_search is a thin wrapper around the GUI search interface on the page https://www.pangaea.de/. Everything you can do there, you can do here.
For example, query for the term 'water', with a bounding box, and return only three results.
pg_search(query = 'water', bbox = c(-124.2, 41.8, -116.8, 46.1), count = 3)
#> # A tibble: 3 x 6
#> score doi size size_measure citation supplement_to
#> <dbl> <chr> <dbl> <chr> <chr> <chr>
#> 1 13.0 10.1594/PANG… 4 datasets Krylova, EM; Sahling, H; Janssen, R (2010): A new genus… Krylova, EM; Sahling, H; Janssen, R (2010): Abyssogena: a new genus of the family …
#> 2 12.8 10.1594/PANG… 2 datasets Simonyan, AV; Dultz, S; Behrens, H (2012): Diffusion tr… Simonyan, AV; Dultz, S; Behrens, H (2012): Diffusive transport of water in porous …
#> 3 8.78 10.1594/PANG… 1148 data points WOCE Surface Velocity Program, SVP (2006): Water temper… <NA>
The resulting data.frame has details about different studies, and you can use the DOIs (Digital Object Identifiers) to get data and metadata for any studies you're interested in.
There's another search option with the pg_search_es function. It is an interface to the Pangaea Elasticsearch interface. This provides a very flexible interface for search Pangaea data - though it is different from what you're used to with the Pangaea website.
(res <- pg_search_es())
#> # A tibble: 10 x 46
#> `_index` `_type` `_id` `_score` `_source.intern… `_source.parent… `_source.minEle… `_source.sf-aut… `_source.parent… `_source.techKe… `_source.geocod… `_source.sp-log…
#> * <chr> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <int> <list> <list> <int>
#> 1 pangaea… panmd 9018… 1 2020-01-17T15:1… https://doi.org… -0.4 Anhaus Philipp#… 901247 <chr [654]> <chr [5]> 1
#> 2 pangaea… panmd 9017… 1 2020-01-17T15:1… https://doi.org… 2 Anhaus Philipp#… 901247 <chr [652]> <chr [5]> 1
#> 3 pangaea… panmd 9017… 1 2020-01-17T15:1… https://doi.org… 2 Anhaus Philipp#… 901247 <chr [652]> <chr [5]> 1
#> 4 pangaea… panmd 9017… 1 2020-01-17T15:1… https://doi.org… 2 Anhaus Philipp#… 901247 <chr [652]> <chr [5]> 1
#> 5 pangaea… panmd 9017… 1 2020-01-17T15:1… <NA> 2 Vuilleumier Lau… NA <chr [51]> <chr [6]> 3
#> 6 pangaea… panmd 9017… 1 2020-01-17T15:1… https://doi.pan… 0.3 Peeken Ilka#Mur… 901742 <chr [101]> <chr [6]> 3
#> 7 pangaea… panmd 9017… 1 2020-01-17T15:1… <NA> NA Schreuder Laura… NA <chr [37]> <chr [3]> 1
#> 8 pangaea… panmd 9017… 1 2020-01-17T15:1… https://doi.org… 0 Schreuder Laura… 901739 <chr [39]> <chr [7]> 1
#> 9 pangaea… panmd 9016… 1 2020-01-17T15:1… <NA> 10 Augustine John$… NA <chr [25]> <chr [6]> 3
#> 10 pangaea… panmd 9016… 1 2020-01-17T15:1… <NA> 2 Augustine John$… NA <chr [29]> <chr [6]> 3
#> # … with 34 more variables: `_source.agg-campaign` <list>, `_source.agg-author` <list>, `_source.eastBoundLongitude` <dbl>, `_source.URI` <chr>, `_source.agg-pubYear` <int>,
#> # `_source.minDateTime` <chr>, `_source.agg-geometry` <chr>, `_source.xml-thumb` <chr>, `_source.xml` <chr>, `_source.sf-idDataSet` <int>, `_source.elevationGeocode` <chr>,
#> # `_source.agg-method` <list>, `_source.maxDateTime` <chr>, `_source.xml-sitemap` <chr>, `_source.westBoundLongitude` <dbl>, `_source.northBoundLatitude` <dbl>,
#> # `_source.sp-dataStatus` <int>, `_source.nDataPoints` <int>, `_source.sp-hidden` <lgl>, `_source.agg-location` <list>, `_source.internal-source` <chr>,
#> # `_source.agg-basis` <chr>, `_source.southBoundLatitude` <dbl>, `_source.boost` <dbl>, `_source.oaiSet` <list>, `_source.maxElevation` <dbl>, `_source.agg-mainTopic` <list>,
#> # `_source.agg-topic` <list>, `_source.agg-project` <list>, `_source.meanPosition.lat` <dbl>, `_source.meanPosition.lon` <dbl>, `_source.geoCoverage.type` <chr>,
#> # `_source.geoCoverage.coordinates` <list>, `_source.geoCoverage.geometries` <list>
The returned data.frame has a lot of columns. You can limit columns returned with the source parameter.
There are attributes on the data.frame that give you the total number of results found as well as the max score found.
attributes(res)
#> $names
#> [1] "_index" "_type" "_id" "_score" "_source.internal-datestamp"
#> [6] "_source.parentURI" "_source.minElevation" "_source.sf-authortitle" "_source.parentIdDataSet" "_source.techKeyword"
#> [11] "_source.geocodes" "_source.sp-loginOption" "_source.agg-campaign" "_source.agg-author" "_source.eastBoundLongitude"
#> [16] "_source.URI" "_source.agg-pubYear" "_source.minDateTime" "_source.agg-geometry" "_source.xml-thumb"
#> [21] "_source.xml" "_source.sf-idDataSet" "_source.elevationGeocode" "_source.agg-method" "_source.maxDateTime"
#> [26] "_source.xml-sitemap" "_source.westBoundLongitude" "_source.northBoundLatitude" "_source.sp-dataStatus" "_source.nDataPoints"
#> [31] "_source.sp-hidden" "_source.agg-location" "_source.internal-source" "_source.agg-basis" "_source.southBoundLatitude"
#> [36] "_source.boost" "_source.oaiSet" "_source.maxElevation" "_source.agg-mainTopic" "_source.agg-topic"
#> [41] "_source.agg-project" "_source.meanPosition.lat" "_source.meanPosition.lon" "_source.geoCoverage.type" "_source.geoCoverage.coordinates"
#> [46] "_source.geoCoverage.geometries"
#>
#> $row.names
#> [1] 1 2 3 4 5 6 7 8 9 10
#>
#> $class
#> [1] "tbl_df" "tbl" "data.frame"
#>
#> $total
#> [1] 390620
#>
#> $max_score
#> [1] 1
attr(res, "total")
#> [1] 390620
attr(res, "max_score")
#> [1] 1
To get to the DOIs for each study, use
gsub("https://doi.org/", "", res$`_source.URI`)
#> [1] "10.1594/PANGAEA.901810" "10.1594/PANGAEA.901736" "10.1594/PANGAEA.901733"
#> [4] "10.1594/PANGAEA.901732" "https://doi.pangaea.de/10.1594/PANGAEA.901710" "https://doi.pangaea.de/10.1594/PANGAEA.901709"
#> [7] "10.1594/PANGAEA.901739" "10.1594/PANGAEA.901738" "https://doi.pangaea.de/10.1594/PANGAEA.901697"
#> [10] "https://doi.pangaea.de/10.1594/PANGAEA.901695"
The function pg_data fetches datasets for studies by their DOIs.
res <- pg_data(doi = '10.1594/PANGAEA.807580')
res[[1]]
#> <Pangaea data> 10.1594/PANGAEA.807580
#> parent doi: 10.1594/PANGAEA.807580
#> url: https://doi.org/10.1594/PANGAEA.807580
#> citation: Schiebel, Ralf; Waniek, Joanna J; Bork, Matthias; Hemleben, Christoph (2001): Physical oceanography during METEOR cruise M36/6. PANGAEA, https://doi.org/10.1594/PANGAEA.807580, In supplement to: Schiebel, R et al. (2001): Planktic foraminiferal production stimulated by chlorophyll redistribution and entrainment of nutrients. Deep Sea Research Part I: Oceanographic Research Papers, 48(3), 721-740, https://doi.org/10.1016/S0967-0637(00)00065-0
#> path: /Users/sckott/Library/Caches/R/pangaear/10_1594_PANGAEA_807580.txt
#> data:
#> # A tibble: 32,179 x 13
#> Event `Date/Time` Latitude Longitude `Elevation [m]` `Depth water [m… `Press [dbar]` `Temp [°C]` Sal `Tpot [°C]` `Sigma-theta [kg/m… `Sigma in situ [kg… `Cond [mS/cm]`
#> <chr> <chr> <dbl> <dbl> <int> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 0 0 15.7 35.7 15.7 26.4 26.4 44.4
#> 2 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 0.99 1 15.7 35.7 15.7 26.4 26.4 44.4
#> 3 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 1.98 2 15.7 35.7 15.7 26.4 26.4 44.4
#> 4 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 2.97 3 15.7 35.7 15.7 26.4 26.4 44.4
#> 5 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 3.96 4 15.7 35.7 15.7 26.4 26.4 44.4
#> 6 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 4.96 5 15.7 35.7 15.7 26.4 26.4 44.4
#> 7 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 5.95 6 15.7 35.7 15.7 26.4 26.4 44.4
#> 8 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 6.94 7 15.7 35.7 15.7 26.4 26.4 44.4
#> 9 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 7.93 8 15.7 35.7 15.7 26.4 26.4 44.4
#> 10 M36/6-CTD-… 1996-10-14T12… 49.0 -16.5 -4802 8.92 9 15.7 35.7 15.7 26.4 26.4 44.4
#> # … with 32,169 more rows
Search for data then pass one or more DOIs to the pg_data function.
res <- pg_search(query = 'water', bbox = c(-124.2, 41.8, -116.8, 46.1), count = 3)
pg_data(res$doi[3])[1:3]
#> [[1]]
#> <Pangaea data> 10.1594/PANGAEA.405695
#> parent doi: 10.1594/PANGAEA.405695
#> url: https://doi.org/10.1594/PANGAEA.405695
#> citation: WOCE Surface Velocity Program, SVP (2006): Water temperature and current velocity from surface drifter SVP_9524470. PANGAEA, https://doi.org/10.1594/PANGAEA.405695
#> path: /Users/sckott/Library/Caches/R/pangaear/10_1594_PANGAEA_405695.txt
#> data:
#> # A tibble: 192 x 10
#> `Date/Time` Latitude Longitude `Depth water [m]` `Temp [°C]` `UC [cm/s]` `VC [cm/s]` `Lat e` `Lon e` Code
#> <chr> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 1995-12-21T18:00 42.9 -125. 0 12.4 NA NA 0.0001 0.0001 1
#> 2 1995-12-22T00:00 42.9 -125. 0 12.4 4.24 -35.2 0 0 1
#> 3 1995-12-22T06:00 42.8 -125. 0 12.4 -7.8 -38.7 0.0002 0.0001 1
#> 4 1995-12-22T12:00 42.7 -125. 0 12.4 -12.7 -23.1 0.0001 0.0001 1
#> 5 1995-12-22T18:00 42.7 -125. 0 12.4 -15.1 -13.7 0 0 1
#> 6 1995-12-23T00:00 42.7 -125. 0 12.3 -24.1 -9.15 0.0001 0.0001 1
#> 7 1995-12-23T06:00 42.7 -125. 0 12.3 -38.4 0.65 0.0001 0.0001 1
#> 8 1995-12-23T12:00 42.7 -125. 0 12.3 -37.2 15.8 0 0 1
#> 9 1995-12-23T18:00 42.7 -125. 0 12.3 -25.4 29.6 0.0001 0.0001 1
#> 10 1995-12-24T00:00 42.8 -125. 0 12.4 -18.5 35.1 0.0002 0.0002 1
#> # … with 182 more rows
#>
#> [[2]]
#> NULL
#>
#> [[3]]
#> NULL
OAI-PMH is a standard protocol for serving metadata around objects, in this case datasets. If you are already familiar with OAI-PMH you are in luck as you can can use what you know here. If not familiar, it's relatively straight-forward.
Note that you can't get data through these functions, rather only metadata about datasets.
pg_identify()
#> <Pangaea>
#> repositoryName: PANGAEA - Data Publisher for Earth & Environmental Science
#> baseURL: https://ws.pangaea.de/oai/provider
#> protocolVersion: 2.0
#> adminEmail: tech@pangaea.de
#> adminEmail: tech@pangaea.de
#> earliestDatestamp: 2015-01-01T00:00:00Z
#> deletedRecord: transient
#> granularity: YYYY-MM-DDThh:mm:ssZ
#> compression: gzip
#> description: oaipangaea.de:oai:pangaea.de:doi:10.1594/PANGAEA.999999
pg_list_metadata_formats()
#> metadataPrefix schema metadataNamespace
#> 1 oai_dc http://www.openarchives.org/OAI/2.0/oai_dc.xsd http://www.openarchives.org/OAI/2.0/oai_dc/
#> 2 pan_md http://ws.pangaea.de/schemas/pangaea/MetaData.xsd http://www.pangaea.de/MetaData
#> 3 dif http://gcmd.gsfc.nasa.gov/Aboutus/xml/dif/dif_v9.4.xsd http://gcmd.gsfc.nasa.gov/Aboutus/xml/dif/
#> 4 iso19139 http://www.isotc211.org/2005/gmd/gmd.xsd http://www.isotc211.org/2005/gmd
#> 5 iso19139.iodp http://www.isotc211.org/2005/gmd/gmd.xsd http://www.isotc211.org/2005/gmd
#> 6 datacite3 http://schema.datacite.org/meta/kernel-3/metadata.xsd http://datacite.org/schema/kernel-3
#> 7 datacite4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd http://datacite.org/schema/kernel-4
pg_list_identifiers(from = Sys.Date() - 2, until = Sys.Date())
pg_list_sets()
#> # A tibble: 282 x 2
#> setSpec setName
#> <chr> <chr>
#> 1 ACD PANGAEA set / keyword 'ACD' (2 data sets)
#> 2 ASPS PANGAEA set / keyword 'ASPS' (59 data sets)
#> 3 AWIXRFraw PANGAEA set / keyword 'AWIXRFraw' (1 data sets)
#> 4 BAH1960 PANGAEA set / keyword 'BAH1960' (2 data sets)
#> 5 BAH1961 PANGAEA set / keyword 'BAH1961' (2 data sets)
#> 6 BAH1962 PANGAEA set / keyword 'BAH1962' (7 data sets)
#> 7 BAH1963 PANGAEA set / keyword 'BAH1963' (7 data sets)
#> 8 BAH1964 PANGAEA set / keyword 'BAH1964' (7 data sets)
#> 9 BAH1965 PANGAEA set / keyword 'BAH1965' (7 data sets)
#> 10 BAH1966 PANGAEA set / keyword 'BAH1966' (6 data sets)
#> # … with 272 more rows
pg_list_records(from = Sys.Date() - 1, until = Sys.Date())
pg_get_record(identifier = "oai:pangaea.de:doi:10.1594/PANGAEA.788382")
#> $`oai:pangaea.de:doi:10.1594/PANGAEA.788382`
#> $`oai:pangaea.de:doi:10.1594/PANGAEA.788382`$header
#> # A tibble: 1 x 3
#> identifier datestamp setSpec
#> <chr> <chr> <chr>
#> 1 oai:pangaea.de:doi:10.1594/PANGAEA.788382 2020-01-18T03:11:42Z citable;supplement;topicChemistry;topicLithosphere
#>
#> $`oai:pangaea.de:doi:10.1594/PANGAEA.788382`$metadata
#> # A tibble: 1 x 13
#> title creator source publisher date type format identifier description language rights coverage subject
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Trace metals in… Demina, Ly… P.P. Shirshov Instit… PANGAEA 2012-… Datas… applic… https://doi.pan… Bioaccumulation of trace… en CC-BY-3.0: … MEDIAN LATITUDE: 29.1… Archive…