Welcome to the Frictionless Data for Reproducible Research Fellows Programme!
Join our upcoming Open Data Day event!
Open Research Data 101: Research Tools and Real-Time Applications.
6th March, 15:00 UTC - 18:00 UTC, online.
Join the Frictionless Data Fellows for an Open Data Day event celebrating open research data. This event will start with a presentation on open science by Dr. Caleb Kibet, followed by an hour-long workshop by the Frictionless Fellows, and culminating in a panel discussing “Balancing Ethics and Open Access Research” featuring Dr. Monica Granados, Cedric Lombion, and Douglas McCarthy. We hope you will join us for this overview of open data in research!
RSVP here for the link to join this virtual event. This event is open to everyone.
What is the Reproducible Research Fellows Programme?
With the Frictionless Data Reproducible Research Fellows Programme, supported by the Sloan Foundation, we are recruiting and training early career researchers to become champions of the Frictionless Data tools and approaches in their field. Fellows will learn about Frictionless Data, including how to use Frictionless tools in their domains to improve reproducible research workflows, and how to advocate for open science. Working closely with the Frictionless Data team, Fellows will lead training workshops at conferences, host events at universities and in labs, and write blogs and other communications content. In addition to mentorship, we are providing successful applicants with stipends of $5,000 to support their work and time during the nine-month long Fellows Programme. The Second Cohort of Fellows begins in August 2020.
The Fellows Programme is part of the Frictionless Data for Reproducible Research project at Open Knowledge Foundation. The first Fellows Cohort took place from Fall 2019 til Spring 2020. This project, funded by the Sloan Foundation, applies our work in Frictionless Data to data-driven research disciplines, in order to facilitate data workflows in research contexts. At its core, Frictionless Data is a set of specifications for data and metadata interoperability, accompanied by a collection of software libraries that implement these specifications, and a range of best practices for data management. The core specification, the Data Package, is a simple and practical “container” for data and metadata.