Interface to 'Virtuoso' using 'ODBC'

Provides users with a simple and convenient mechanism to manage and query a 'Virtuoso' database using the 'DBI' (DataBase Interface) compatible 'ODBC' (Open Database Connectivity) interface. 'Virtuoso' is a high-performance "universal server," which can act as both a relational database, supporting standard Structured Query Language ('SQL') queries, while also supporting data following the Resource Description Framework ('RDF') model for Linked Data. 'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language) queries, a graph-based query that supports semantic reasoning. This allows users to leverage the performance of local or remote 'Virtuoso' servers using popular 'R' packages such as 'DBI' and 'dplyr', while also providing a high-performance solution for working with large 'RDF' triplestores from 'R.' The package also provides helper routines to install, launch, and manage a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using the standard interactive installers from the 'R' command-line. By automatically handling these setup steps, the package can make using 'Virtuoso' considerably faster and easier for a most users to deploy in a local environment. Managing the bulk import of triples from common serializations with a single intuitive command is another key feature of this package. Bulk import performance can be tens to hundreds of times faster than the comparable imports using existing 'R' tools, including 'rdflib' and 'redland' packages.


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Reference manual

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install.packages("virtuoso")

0.1.3 by Carl Boettiger, 6 months ago


https://github.com/ropensci/virtuoso


Report a bug at https://github.com/ropensci/virtuoso/issues


Browse source code at https://github.com/cran/virtuoso


Authors: Carl Boettiger [aut, cre, cph] , Bryce Mecum [ctb]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports odbc, processx, DBI, utils, ini, rappdirs, curl, fs, digest, ps

Suggests knitr, rmarkdown, nycflights13, testthat, covr, jsonld, dplyr, spelling


See at CRAN