Title: Open Source Initiative API Connector
Description: A connector to the API maintained by the Open Source Initiative <https://api.opensource.org/licenses/>, which
provides machine-readable metadata about a variety of open source software licenses.
Packaged: 2016-06-20 23:42:20 UTC; ironholds

Title: Raw System Credential Store Access from R
Description: Aims to support all features of the system credential store,
including non-portable ones. Supports 'Keychain' on 'macOS',
and 'Credential Manager' on 'Windows'. See the 'keyring' package if you
Packaged: 2020-10-22 07:57:30 UTC; gaborcsardi

Packaged: 2020-11-09 10:19:07 UTC; gaborcsardi

Packaged: 2021-11-17 14:58:01 UTC; gaborcsardi

Packaged: 2022-03-11 12:00:40 UTC; gaborcsardi

including non-portable ones. Supports 'Keychain' on 'macOS', and
'Credential Manager' on 'Windows'. See the 'keyring' package if you
Suggests: askpass, covr, testthat (>= 3.0.0), withr
Packaged: 2022-09-08 09:23:32 UTC; gaborcsardi

Packaged: 2022-10-27 10:05:46 UTC; gaborcsardi

Title: Importing and working with OpenStreetMap-Data
Author: Thomas Schlesinger and Manuel Eugster
Description: This package imports the (Spatial and Non-Spatial) Data of
OpenStreetMap into objects of R by using the OSM-API v0.6. For
now it is reduced on using various commands of type "GET", like
getting data of an explicit element or a region defined by
coordinates. It also includes some methods on working with the

Author: Thomas Schlesinger and Manuel J. A. Eugster
Description: This package provides infrastructure to access
OpenStreetMap data from different sources, to work with the
data in common R manner, and to convert data into available
infrastructure provided by existing R packages (e.g., into sp
Depends: methods, XML, RCurl, gtools, geosphere
'source.R' 'get.R' 'osmar.R' 'source-api.R' 'source-osmosis.R'

Depends: R (>= 2.10), methods, XML, RCurl, gtools, geosphere
'as-osmar-elements.R' 'as-osmar.R' 'as-osm.R' 'as-sp.R' 'get.R'

Packaged: 2012-09-12 06:43:03 UTC; mjaeugster

OpenStreetMap data from different sources, to work with the data
in common R manner, and to convert data into available
infrastructure provided by existing R packages (e.g., into sp and