rdpla tutorial
for v0.2.0
rdpla: R client for Digital Public Library of America
Digital Public Library of America brings together metadata from libraries, archives, and museums in the US, and makes it freely available via their web portal as well as an API. DPLA’s portal and API don’t provide the items themselves from contributing institutions, but they provide links to make it easy to find things. The kinds of things DPLA holds metadata for include images of works held in museums, photographs from various photographic collections, texts, sounds, and moving images.
DPLA has a great API with good documentation - a rare thing in this world. Further documentation on their API can be found on their search fields and examples of queries. Metadata schema information here.
DPLA API has two main services (quoting from their API docs):
- items: A reference to the digital representation of a single piece of content indexed by
the DPLA. The piece of content can be, for example, a book, a photograph, a video, etc. The
content is digitized from its original, physical source and uploaded to an online repository.
items are available in the
dpla_items()function. - collections: A collection is a little more abstract than an item. Where an item is a
reference to the digital representation of a physical object, a collection is a
representation of the grouping of a set of items. collections are available in the
dpla_collections()function.
Note that you can only run examples/vignette/tests if you have an API key. See below for an example of how to get an API key.
Installation
Stable version from CRAN
install.packages("rdpla")
Development version from GitHub
if (!require("devtools")) install.packages("devtools")
devtools::install_github("ropensci/rdpla")
library("rdpla")
Usage
API key
If you already have a DPLA API key, make sure it’s in your .Renviron or .Rprofile file.
If you don’t have a DPLA API key, use the dpla_get_key() function to get a key.
You only need a valid email address to get a key, for example:
dpla_get_key(email = "foo@bar.com")
#> API key created and sent via email. Be sure to check your Spam folder, too.
Search - items
Note: limiting fields returned for readme brevity.
Basic search
dpla_items(q="fruit", page_size=5, fields=c("provider","creator"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 42020 0 5
#>
#> $data
#> # A tibble: 5 x 2
#> provider creator
#> <chr> <chr>
#> 1 Mountain West Digital Library no content
#> 2 Mountain West Digital Library no content
#> 3 Mountain West Digital Library no content
#> 4 Mountain West Digital Library no content
#> 5 Mountain West Digital Library no content
#>
#> $facets
#> list()
Limit fields returned
dpla_items(q="fruit", page_size = 10, fields=c("publisher","format"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 42020 0 10
#>
#> $data
#> # A tibble: 10 x 2
#> format publisher
#> <chr> <chr>
#> 1 no content no content
#> 2 no content no content
#> 3 no content no content
#> 4 no content no content
#> 5 no content no content
#> 6 no content no content
#> 7 no content no content
#> 8 no content no content
#> 9 no content no content
#> 10 no content no content
#>
#> $facets
#> list()
Limit records returned
dpla_items(q="fruit", page_size=2, fields=c("provider","title"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 42020 0 2
#>
#> $data
#> # A tibble: 2 x 2
#> title provider
#> <chr> <chr>
#> 1 Fruit Mountain West Digital Library
#> 2 Fruit Mountain West Digital Library
#>
#> $facets
#> list()
Search by date
dpla_items(q="science", date_before=1900, page_size=10, fields=c("id","date"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 57981 0 10
#>
#> $data
#> # A tibble: 10 x 2
#> id date
#> <chr> <chr>
#> 1 e0f460c6d710c125c7ba6d5186b076e4 1896
#> 2 fd0710105d8a7a49b87d956364289d7d 1891
#> 3 e3f11047a57f18f8a21baf5d6ff3c4dd 1886
#> 4 cf718498ee3b9886da35a43566a6a121 1887
#> 5 e8f0ed10dbdcd0ffd6f504e1892515da 1885
#> 6 db59f79180d11c22117cd49f728a1f19 1880
#> 7 d8421296829e9e8e041e2841118a4651 1890
#> 8 1ddac8df735b31b13f0032a7b8293abf 1890
#> 9 dd7e219e625ba0609d9062182029a78c 1880
#> 10 8177b82cc0542e1895fe92718e6c93da 1892
#>
#> $facets
#> list()
Search on specific fields
dpla_items(description="obituaries", page_size=2, fields="description")
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 51276 0 2
#>
#> $data
#> # A tibble: 2 x 1
#> description
#> <chr>
#> 1 Obituaries of members
#> 2 Pages from the complied obituaries
#>
#> $facets
#> list()
dpla_items(subject="yodeling", page_size=2, fields="subject")
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 54 0 2
#>
#> $data
#> # A tibble: 2 x 1
#> subject
#> <chr>
#> 1 Yodeling--Austria;Musicians--Austria;Gamehouses--Austria
#> 2 Yodeling--Austria;Musicians--Austria;Gamehouses--Austria
#>
#> $facets
#> list()
dpla_items(provider="HathiTrust", page_size=2, fields="provider")
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 2673588 0 2
#>
#> $data
#> # A tibble: 2 x 1
#> provider
#> <chr>
#> 1 HathiTrust
#> 2 HathiTrust
#>
#> $facets
#> list()
Spatial search, across all spatial fields
dpla_items(sp='Boston', page_size=2, fields=c("id","provider"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 64121 0 2
#>
#> $data
#> # A tibble: 2 x 2
#> id provider
#> <chr> <chr>
#> 1 41aa36a38d69f5247529505a55528b5d Smithsonian Institution
#> 2 337556aaa3096bd77e462d898b70c9d7 Smithsonian Institution
#>
#> $facets
#> list()
Spatial search, by states
dpla_items(sp_state='Massachusetts OR Hawaii', page_size=2, fields=c("id","provider"))
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 203299 0 2
#>
#> $data
#> # A tibble: 2 x 2
#> id
#> <chr>
#> 1 3d3fba16636ab5211a10ff0b0bf44ae6
#> 2 8e2e5f685b4dd0af109fb32fb3db7f1c
#> # ... with 1 more variables: provider <chr>
#>
#> $facets
#> list()
Faceted search
dpla_items(facets=c("sourceResource.spatial.state","sourceResource.spatial.country"),
page_size=0, facet_size=5)
#> $meta
#> # A tibble: 1 x 3
#> found start returned
#> <int> <int> <int>
#> 1 17857065 0 0
#>
#> $data
#> # A tibble: 0 x 0
#>
#> $facets
#> $facets$sourceResource.spatial.state
#> $facets$sourceResource.spatial.state$meta
#> # A tibble: 1 x 4
#> type total missing other
#> <chr> <int> <int> <int>
#> 1 terms 6586777 12065850 3837491
#>
#> $facets$sourceResource.spatial.state$data
#> # A tibble: 5 x 2
#> term count
#> <chr> <int>
#> 1 Texas 900822
#> 2 California 652773
#> 3 Georgia 508989
#> 4 New York 486016
#> 5 Utah 200686
#>
#>
#> $facets$sourceResource.spatial.country
#> $facets$sourceResource.spatial.country$meta
#> # A tibble: 1 x 4
#> type total missing other
#> <chr> <int> <int> <int>
#> 1 terms 8248758 10554280 2095768
#>
#> $facets$sourceResource.spatial.country$data
#> # A tibble: 5 x 2
#> term count
#> <chr> <int>
#> 1 United States 5512055
#> 2 Russia 178623
#> 3 Mexico 171047
#> 4 France 147943
#> 5 Poland 143322
Search - collections
Search for collections with the words university of texas
dpla_collections(q="university of texas", page_size=2)
#> $meta
#> # A tibble: 1 x 2
#> found returned
#> <int> <int>
#> 1 18 2
#>
#> $data
#> # A tibble: 2 x 14
#> `_rev` ingestDate
#> <chr> <chr>
#> 1 14-bb5f3466c0a1e579974ef94d49a5cc85 2017-10-04T02:42:01.229088Z
#> 2 15-339f2d764716ad98af19a1f4e975e597 2017-10-04T02:41:52.940499Z
#> # ... with 12 more variables: `@context` <chr>, id <chr>, title <chr>,
#> # `_id` <chr>, description <chr>, `@type` <chr>, ingestType <chr>,
#> # `@id` <chr>, ingestionSequence <int>, score <dbl>,
#> # validation_message <lgl>, valid_after_enrich <lgl>
You can also search in the title and description fields
dpla_collections(description="east")
#> $meta
#> # A tibble: 1 x 2
#> found returned
#> <int> <int>
#> 1 3 10
#>
#> $data
#> # A tibble: 3 x 14
#> `_rev` ingestDate
#> <chr> <chr>
#> 1 10-3902841b19a1e2ff9f7d0f50e341b084 2017-08-22T23:08:25.766144Z
#> 2 5-9ca83dafb7bcf7087fd561c754e0a509 2017-10-06T20:16:03.681488Z
#> 3 5-48301bd7615558ed90013b3765ead2e5 2017-10-06T20:15:56.314996Z
#> # ... with 12 more variables: `@context` <chr>, id <chr>, title <chr>,
#> # `_id` <chr>, description <chr>, `@type` <chr>, ingestType <chr>,
#> # `@id` <chr>, ingestionSequence <int>, score <dbl>,
#> # validation_message <lgl>, valid_after_enrich <lgl>
Visualize
Visualize metadata from the DPLA - histogram of number of records per state (includes states outside the US)
out <- dpla_items(facets="sourceResource.spatial.state", page_size=0, facet_size=25)
library("ggplot2")
library("scales")
ggplot(out$facets$sourceResource.spatial.state$data, aes(reorder(term, count), count)) +
geom_bar(stat="identity") +
coord_flip() +
theme_grey(base_size = 16) +
scale_y_continuous(labels = comma) +
labs(x="State", y="Records")
Citing
Scott Chamberlain (2017). rdpla: Client for the Digital Public Library of America (‘DPLA’). R package version 0.2.0. https://CRAN.R-project.org/package=rdpla
License and bugs
- License: MIT
- Report bugs at our GitHub repo for rdpla
