As part of our commitment to opening up scientific knowledge, we recently launched the Frictionless Data for Reproducible Research Fellows Programme (opens new window), which will run from mid-September until June 2020.
We received over 200 impressive applications for the Programme, and are very excited to introduce the four selected Fellows:
Monica Granados, a Mitacs Canadian Science Policy Fellow;
Selene Yang, a graduate student researcher at the National University of La Plata, Argentina;
Daniel Ouso, a postgraduate researcher at the International Centre of Insect Physiology and Ecology;
Lily Zhao, a graduate student researcher at the University of California, Santa Barbara.
Next month, the Fellows will be writing blogs to further introduce themselves to the Frictionless Data community, so stay tuned to learn more about these impressive researchers.
The Programme will train 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.
As the programme progresses, we will be sharing the Fellows’ work on making research more reproducible with the Frictionless Data software suite by posting a series of blogs here and on the Fellows website (opens new window). In June 2020, the Programme will culminate in a community call where all Fellows will present what they have learned over the nine months: we encourage attendance by our community. If you are interested in learning more about the Programme, the syllabus (opens new window), lessons (opens new window), and resources (opens new window) are open.
# More About Frictionless Data
The Fellows Programme is part of the Frictionless Data for Reproducible Research project at Open Knowledge Foundation. 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. 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. Frictionless Data’s other current projects include the Tool Fund (opens new window), in which four grantees are developing open source tooling for reproducible research. The Fellows Programme will be running until June 2020, and we will post updates to the Programme as they progress.