English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Many interesting data sets available on the Internet are of a mediumsize---too big to fit into a personal computer's memory, but not so large thatthey won't fit comfortably on its hard disk. In the coming years, data sets ofthis magnitude will inform vital research in a wide array of applicationdomains. However, due to a variety of constraints they are cumbersome toingest, wrangle, analyze, and share in a reproducible fashion. Theseobstructions hamper thorough peer-review and thus disrupt the forward progressof science. We propose a predictable and pipeable framework for R (thestate-of-the-art statistical computing environment) that leverages SQL (thevenerable database architecture and query language) to make reproducibleresearch on medium data a painless reality.

A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data