The Journal of Open Source Software

A developer friendly journal for research software packages.

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ropensci / jstor

Functions and helpers to import metadata, n-grams and full-texts delivered by Data for Research (DfR) by JSTOR.

The package has been reviewed and accepted by rOpenSci.

williamsbenjamin / blendR

This R package (blendR) gives four estimators for combining a non-probability sample with a probability sample, in a capture-recapture sample setting, and example data from Texas Parks and...

j-andrews7 / Genotify

Genotify collates gene annotation data from dozens of data sources to quickly provide a comprehensive overview of a gene's function, expression patterns, disease associations, and more in one...

vsoch / containershare

Containershare is an open source library of containers and template software to serve discoverable image metadata, inspection, and version controlled containers.

rrrlw / TDAstats

TDAstats is an R package that provides a faster and more comprehensive pipeline for topological data analysis than is currently available (in any programming language). It has three main functions:...

ropensci / nomisr

An R interface to access UK official labour market statistics and census data from the 'Nomis' database, based around statistical geographies.

andrewthomasjones / logKDE

The goal of logKDE is to provide a set of functions for kernel density estimation on the positive domain, using log-kernel density functions, for the R programming environment. In order to...

lumenlearning / rise

The RISE package leverages student learning data and course design data to help designers of educational materials identify portions of their courses that are not effectively supporting student...

vincentarelbundock / countrycode

Government agencies and research labs use different codes to identify countries, which can be a headache for analysts who need to merge datasets from different sources. This package helps...

sdtaylor / pyPhenology

A package for building, evaluating, and making predictions using process based plant phenology models.

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