An R package for retrieving official data on European Union law.


Install from CRAN via install.packages("eurlex").

The development version is available via remotes::install_github("michalovadek/eurlex").


The eurlex R package attempts to significantly reduce the overhead associated with using SPARQL and REST APIs made available by the EU Publication Office. Although at present it does not offer access to the same array of information as comprehensive web scraping might, the package provides simpler, more efficient and transparent access to data on European Union law.

The eurlex package currently envisions the typical use-case to consist of getting bulk information about EU legislation into R as fast as possible. The package contains three core functions to achieve that objective: elx_make_query() to create pre-defined or customized SPARQL queries; elx_run_query() to execute the pre-made or any other manually input query; and elx_fetch_data() to fire GET requests for certain metadata to the REST API.

The function elx_make_query takes as its first argument the type of resource to be retrieved (such as “directive”) from the semantic database that powers Eur-Lex (and other publications) called Cellar. If you are familiar with SPARQL, you can always specify your own queries and execute them with elx_run_query().

elx_run_query() executes SPARQL queries on a pre-specified endpoint of the EU Publication Office. It outputs a data.frame where each column corresponds to one of the requested variables, while the rows accumulate observations of the resource type satisfying the query criteria. Obviously, the more data is to be returned, the longer the execution time, varying from a few seconds to several hours, depending also on your connection. The first column always contains the unique URI of a “work” (legislative act or court judgment) which identifies each resource in Cellar. Several human-readable identifiers are normally associated with each “work” but the most useful one is CELEX, retrieved by default.

For the moment, it is recommended to retrieve metadata one variable at a time. For example, if you wish to obtain the legal bases of directives and the date of transposition, you should run separate calls:

  1. ids <- elx_make_query("directive") %>% elx_run_query()
  2. lbs <- elx_make_query("directive", include_lbs = TRUE) %>% elx_run_query()
  3. dates <- elx_make_query("directive", include_date_transpos = TRUE) %>% elx_run_query()
  4. ids %>% dplyr::left_join(lbs) %>% dplyr::left_join(dates)

rather than elx_make_query("directive", include_lbs = TRUE, include_date_transpos = TRUE). This approach should make it easier to understand the returned data frame(s), especially when some variables contain missing or duplicated data.

One of the main contributions of the SPARQL requests is that we obtain a comprehensive list of identifiers that we can subsequently use to obtain more data relating to the document in question. While the results of the SPARQL queries are useful also for webscraping (with the rvest package), the function elx_fetch_data() enables us to fire GET requests to retrieve data on documents with known identifiers (including Cellar URI). The function currently enables downloading the title and the full text of a document in all available languages.

See the vignette for a walkthrough on how to use the package. Check function documentation for most up-to-date overview of features.


Michal Ovádek (2020). eurlex: An R package for retrieving official data on European Union law


This package nor its author are in any way affiliated with the EU Publications Office. Please refer to the applicable data reuse policies.

Please consider contributing to the maintanance and development of the package by reporting bugs or suggesting new features.