rsdmx
rsdmx
: Tools for reading SDMX data and metadata documents in R
Overview
rsdmx
is a package to parse/read SDMX data and metadata in R. It provides:
- a set of classes and methods to read data and metadata documents exchanged through the Statistical Data and Metadata Exchange (SDMX) framework. The package currently focuses on the SDMX XML standard format (SDMX-ML).
- an interface to SDMX web-services for a list of well-known data providers, such as EUROSTAT, OECD, and others
Citation
We thank in advance people that use rsdmx
for citing it in their work / publication(s). For this, please use the citation provided at this link
Collating scattered SDMX data sources
In spite they are some R package initiatives relying on rsdmx
that aim to provide a wrapper for a single data source (e.g. OECD, EUROSTAT), it is strongly recommended to rely directly on rsdmx
. Indeed, one main objective of rsdmx
is to promote and facilitate collating scattered data from a growing number of SDMX data providers, whatever the organization.
It is already possible to query well-known datasources, using the embedded helpers. Pull requests are welcome to support additional data providers by default in rsdmx
.
SDMX standards compliance
Status
At now, the package allows to read:
- Datasets (
GenericData
,CompactData
,StructureSpecificData
,StructureSpecificTimeSeriesData
,CrossSectionalData
,UtilityData
andMessageGroup
SDMX-ML types) - Concepts (
Concept
,ConceptScheme
andConcepts
SDMX-ML types) - Codelists (
Code
,Codelist
andCodelists
SDMX-ML types) - DataStructures / KeyFamilies - with all subtypes
- Data Structure Definitions (DSDs) - with all subtypes
Fundings
rsdmx
is looking for sponsors. You have been using rsdmx
and you wish to support its development? Please help us to make the package growing!
Author
Copyright (C) 2014 Emmanuel Blondel
Contributors
- Matthieu Stigler
- Eric Persson
Distribution
on CRAN
rsdmx
is available on the Comprehensive R Archive Network (CRAN). See the R CRAN check results at: https://cran.r-project.org/web/checks/check_results_rsdmx.html
Please note that following a new submission to CRAN, or eventually a modification of CRAN policies, the package might be temporarily archived, and removed from CRAN. In case you notice that the package is not back in few time, please contact me.
on R-Universe
rsdmx
is available on the R-Universe public cloud server. The package version corresponds to the ongoing revision (master branch in Github). See https://opensdmx.r-universe.dev/#package:rsdmx
Quickstart
rsdmx offers a low-level set of tools to read data and metadata in SDMX format. Its strategy is to make it very easy for the user. For this, a unique function named readSDMX
has to be used, whatever it is a data
or metadata
document, or if it is local
or remote
datasource.
It is important to highlight that one of the major benefits of rsdmx
is to focus first on the SDMX format specifications (acting as format abstraction library). This allows rsdmx
reading SDMX data from remote datasources, or from local SDMX files. For accessing remote datasources, it also means that rsdmx
does not bound to SDMX service specifications, and can read a wider ranger of datasources.
Install rsdmx
rsdmx
can be installed from CRAN
install.packages("rsdmx")
or from its development repository hosted in Github (using the devtools
package):
devtools::install_github("opensdmx/rsdmx")
Load rsdmx
To load rsdmx in R, do the following:
library(rsdmx)
readSDMX & helper functions
readSDMX as low-level function
The readSDMX
function is then first designed at low-level so it can take as parameters a url (isURL=TRUE
by default) or a file. So wherever is located the SDMX document, readSDMX
will allow you to read it, as follows:
#read a remote file
sdmx <- readSDMX(file = "someUrl")
#read a local file
sdmx <- readSDMX(file = "somelocalfile", isURL = FALSE)
In addition, in order to facilitate querying datasources, readSDMX
also providers helpers to query well-known remote datasources. This allows not to specify the entire URL, but rather specify a simple provider ID, and the different parameters to build a SDMX query (e.g. for a dataset query: operation, key, filter, startPeriod and endPeriod).
This is made possible as a list of SDMX service providers is embedded within rsdmx
, and such list provides all the information required for readSDMX
to build the SDMX request (url) before accessing the datasource.
get list of SDMX service providers
The list of known SDMX service providers can be queried as follows:
providers <- getSDMXServiceProviders()
as.data.frame(providers)
create/add a SDMX service provider
It also also possible to create and add a new SDMX service providers in this list (so readSDMX
can be aware of it). A provider can be created with the SDMXServiceProvider
, and is made of various parameters:
agencyId
(provider identifier)name
scale
(international or national)country
ISO 3-alpha code (if national)builder
The request builder can be created with SDMXRequestBuilder
which takes various arguments:
regUrl
: URL of the service registry endpointrepoUrl
: URL of the service repository endpoint (Note that we use 2 different
arguments for registry and repository endpoints, since some providers use different URLs, but in most cases those are identical)
formatter
list of functions to format the request params (one function per
type of resource, e.g. "dataflow", "datastructure", "data")
handler
list of functions which will allow to build the web request
*compliant
logical parameter (either the request builder is compliant with some web-service specifications)
rsdmx
yet provides common builders, that can be customized if needed, by overriding
either the formatter
or the handler
functions:
SDMXREST20RequestBuilder
: connector for SDMX REST 2.0 web-servicesSDMXREST21RequestBuilder
: connector for SDMX REST 2.1 web-servicesSDMXDotStatRequestBuilder
: connector for SDMX .Stat ("DotStat") web-services implementations
Let's see it with an example:
First create a request builder for our provider:
myBuilder <- SDMXRequestBuilder(
regUrl = "http://www.myorg.org/sdmx/registry",
repoUrl = "http://www.myorg.org/sdmx/repository",
formatter = list(
dataflow = function(obj){
#format each dataflow id with some prefix
obj@resourceId <- paste0("df_",obj@resourceId)
return(obj)
},
datastructure = function(obj){
#do nothing
return(obj)
},
data = function(obj){
#format each dataset id with some prefix
obj@flowRef <- paste0("data_",obj@flowRef)
return(obj)
}
),
handler = list(
dataflow = function(obj){
req <- sprintf("%s/dataflow",obj@regUrl)
return(req)
},
datastructure = function(obj){
req <- sprintf("%s/datastructure",obj@regUrl)
return(req)
},
data = function(obj){
req <- sprintf("%s/data",obj@regUrl)
return(req)
}
),
compliant = FALSE
)
As you can see, we built a custom SDMXRequestBuilder
that will be able to
create SDMX web-requests for the different resources of a SDMX web-service.
We can create a provider with the above request builder, and add it to the list of known SDMX service providers:
#create the provider
provider <- SDMXServiceProvider(
agencyId = "MYORG",
name = "My Organization",
builder = myBuilder
)
#add it to the list
addSDMXServiceProvider(provider)
#check provider has been added
as.data.frame(getSDMXServiceProviders())
find a SDMX service provider
A another helper allows you to interrogate rsdmx
if a specific provider is
known, given an id:
oecd <- findSDMXServiceProvider("OECD")
readSDMX as helper function
Now you know how to add a SDMX provider, you can consider using readSDMX
without having to specifying a entire URL, but just by specifying the agencyId
of the provider, and the different query parameters to reach your SDMX document:
sdmx <- readSDMX(providerId = "MYORG", providerKey = NULL resource = "data", flowRef="MYSERIE",
key = "all", key.mode = "SDMX", start = 2000, end = 2015)
For embedded service providers that require a user authentication/subscription key or token,
it is possible to specify it in readSDMX
with the providerKey
argument. If provided,
and that the embedded provider requires a specific key parameter, the latter will be appended
to the SDMX web-request.
The following sections will show you how to query SDMX documents, by using readSDMX
in different ways: either for local or remote files, using readSDMX
as low-level
or with the helpers (embedded service providers).
Read dataset documents
This section will introduce you on how to read SDMX dataset documents.
Read remote datasets
The following code snipet shows you how to read a dataset from a remote data source, taking as example the OECD StatExtracts portal: https://sdmx.oecd.org/public/rest/data/DSD_PRICES@DF_PRICES_N_CP01/GRC......./all/?startPeriod=2020&endPeriod=2020
myUrl <- "https://sdmx.oecd.org/public/rest/data/DSD_PRICES@DF_PRICES_N_CP01/GRC......./all/?startPeriod=2020&endPeriod=2020"
dataset <- readSDMX(myUrl)
stats <- as.data.frame(dataset)
You can try it out with other datasources, such as:
- EUROSTAT portal: [https://ec.europa.eu/eurostat/SDMX/diss-web/rest/data/nama_10_gdp/.CLV10_MEUR.B1GQ.BE/?startperiod=2005&endPeriod=2011)
- European Central Bank (ECB): https://sdw-wsrest.ecb.europa.eu/service/data/DD/M.SE.BSI_STF.RO.4F_N
The online rsdmx documentation also provides a list of data providers, either from international or national institutions.
Now, the service providers above mentioned are known by rsdmx
which let users using readSDMX
with the helper parameters. It may also be the case for a provider that
you register in rsdmx.
Let's see how it would look like for querying an OECD
datasource:
sdmx <- readSDMX(providerId = "OECD", resource = "data", flowRef = "DSD_PRICES@DF_PRICES_N_CP01",
key = list("GRC", NULL, NULL, NULL, NULL, NULL, NULL, NULL), start = 2020, end = 2020)
df <- as.data.frame(sdmx)
head(df)
It is also possible to query a dataset together with its "definition", handled
in a separate SDMX-ML document named DataStructureDefinition
(DSD). It is
particularly useful when you want to enrich your dataset with all labels. For this,
you need the DSD which contains all reference data.
To do so, you only need to append dsd = TRUE
(default value is FALSE
),
to the previous request, and specify labels = TRUE
when calling as.data.frame
,
as follows:
sdmx <- readSDMX(providerId = "OECD", resource = "data", flowRef = "DSD_PRICES@DF_PRICES_N_CP01",
key = list("GRC", NULL, NULL, NULL, NULL, NULL, NULL, NULL), start = 2020, end = 2020,
dsd = TRUE)
df <- as.data.frame(sdmx, labels = TRUE)
head(df)
Note that in case you are reading SDMX-ML documents with the native approach (with
URLs), instead of the embedded providers, it is also possible to associate a DSD
to a dataset by using the function setDSD
. Let's try how it works:
#data without DSD
sdmx.data <- readSDMX(providerId = "OECD", resource = "data", flowRef = "DSD_PRICES@DF_PRICES_N_CP01",
key = list("GRC", NULL, NULL, NULL, NULL, NULL, NULL, NULL), start = 2020, end = 2020)
#DSD
sdmx.dsd <- readSDMX(providerId = "OECD", resource = "datastructure", resourceId = "DSD_PRICES")
#associate data and dsd
sdmx.data <- setDSD(sdmx.data, sdmx.dsd)
Read local datasets
This example shows you how to use rsdmx
with local SDMX files, previously downloaded from EUROSTAT.
#bulk download from Eurostat
tf <- tempfile(tmpdir = tdir <- tempdir()) #temp file and folder
download.file("https://ec.europa.eu/eurostat/estat-navtree-portlet-prod/BulkDownloadListing?sort=1&file=data%2Frd_e_gerdsc.sdmx.zip", tf)
sdmx_files <- unzip(tf, exdir = tdir)
sdmx <- readSDMX(sdmx_files[2], isURL = FALSE)
stats <- as.data.frame(sdmx)
head(stats)
By default, readSDMX
considers the data source is remote. To read a local file, add isURL = FALSE
.
Read metadata documents
This section will introduce you on how to read SDMX metadata complete data structure definitions
(DSD)
#### Data Structure Definition (DSD)
This example illustrates how to read a complete DSD using a [OECD StatExtracts portal](https://data-explorer.oecd.org/) data source.
```{r, echo = FALSE}
dsdUrl <- "https://sdmx.oecd.org/public/rest/datastructure/all/DSD_PRICES/latest/?references=children"
dsd <- readSDMX(dsdUrl)
rsdmx
is implemented in object-oriented way with S4
classes and methods. The properties of S4
objects are named slots
and can be accessed with the slot
method. The following code snippet allows to extract the list of codelists
contained in the DSD document, and read one codelist as data.frame
.
#get codelists from DSD
cls <- slot(dsd, "codelists")
codelists <- sapply(slot(cls, "codelists"), function(x) slot(x, "id")) #get list of codelists
codelist <- as.data.frame(slot(dsd, "codelists"), codelistId = "CL_TRANSFORMATION") #get a codelist
In a similar way, the concepts
of the dataset can be extracted from the DSD and read as data.frame
.
#get concepts from DSD
concepts <- as.data.frame(slot(dsd, "concepts"))
Save & Reload SDMX R objects
It is possible to save SDMX R objects as RData file (.RData, .rda, .rds), to then be able to reload them into the R session. It could be of added value for users that want to keep their SDMX objects in R data files, but also for fast loading of large SDMX objects (e.g. DSD objects) for use in statistical analyses and R-based web-applications.
To save a SDMX R object to RData file:
saveSDMX(sdmx, "tmp.RData")
To reload a SDMX R object from RData file:
sdmx <- readSDMX("tmp.RData", isRData = TRUE)