'Microsoft Academic' API Client

The 'Microsoft Academic Knowledge' API provides programmatic access to scholarly articles in the 'Microsoft Academic Graph' (< https://academic.microsoft.com/>). Includes methods matching all 'Microsoft Academic' API routes, including search, graph search, text similarity, and interpret natural language query string.

Read Data from the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) and Australian Bureau of Statistics (ABS)

Download and import agricultural data from the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) < https://www.agriculture.gov.au/abares> and Australian Bureau of Statistics (ABS) < https://www.abs.gov.au>. Data types serviced include spreadsheets, comma separated value (CSV) files, geospatial data including shape files and geotiffs covering topics including broadacre crops, livestock, soil data, commodities and more. Unifies field names and formats for data interoperability making analysis easier by standardising names between data formats. Also simplifies importing geospatial data as well as correcting issues in the geospatial data upon import.

Setup, Run and Analyze 'NetLogo' Model Simulations from 'R' via 'XML'

Setup, run and analyze 'NetLogo' (< https://www.netlogo.org>) model simulations in 'R'. 'nlrx' experiments use a similar structure as 'NetLogos' Behavior Space experiments. However, 'nlrx' offers more flexibility and additional tools for running and analyzing complex simulation designs and sensitivity analyses. The user defines all information that is needed in an intuitive framework, using class objects. Experiments are submitted from 'R' to 'NetLogo' via 'XML' files that are dynamically written, based on specifications defined by the user. By nesting model calls in future environments, large simulation design with many runs can be executed in parallel. This also enables simulating 'NetLogo' experiments on remote high performance computing machines. In order to use this package, 'Java' and 'NetLogo' (>= 5.3.1) need to be available on the executing system.

R Bindings for 'Selenium WebDriver'

Provides a set of R bindings for the 'Selenium 2.0 WebDriver' (see < https://www.selenium.dev/documentation/> for more information) using the 'JsonWireProtocol' (see < https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more information). 'Selenium 2.0 WebDriver' allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.

Access 'EMODnet' Web Feature Service Data

Access and interrogate 'EMODnet' (European Marine Observation and Data Network) Web Feature Service data < https://emodnet.ec.europa.eu/en/emodnet-web-service-documentation#data-download-services>. This includes listing existing data sources, and getting data from each of them.

Interface to the Search API for 'PLoS' Journals

A programmatic interface to the 'SOLR' based search API (< http://api.plos.org/>) provided by the Public Library of Science journals to search their articles. Functions are included for searching for articles, retrieving articles, making plots, doing 'faceted' searches, 'highlight' searches, and viewing results of 'highlighted' searches in a browser.

Geocode with the OpenCage API

Geocode with the OpenCage API, either from place name to longitude and latitude (forward geocoding) or from longitude and latitude to the name and address of a location (reverse geocoding), see < https://opencagedata.com/>.

Extract and Tidy Canadian 'Hydrometric' Data

Provides functions to access historical and real-time national 'hydrometric' data from Water Survey of Canada data sources and then applies tidy data principles.

Control 'BEAST2'

'BEAST2' (< https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAST2' is commonly accompanied by 'BEAUti 2', 'Tracer' and 'DensiTree'. 'babette' provides for an alternative workflow of using all these tools separately. This allows doing complex Bayesian phylogenetics easily and reproducibly from 'R'.

Reproducible Data Science Environments with 'Nix'

Simplifies the creation of reproducible data science environments using the 'Nix' package manager, as described in Dolstra (2006) . The included `rix()` function generates a complete description of the environment as a `default.nix` file, which can then be built using 'Nix'. This results in project specific software environments with pinned versions of R, packages, linked system dependencies, and other tools or programming languages such as Python or Julia. Additional helpers make it easy to run R code in 'Nix' software environments for testing and production.