Join us on 20th May at 4pm BST/10am CDT for a Frictionless Data workshop led by the Reproducible Research fellows. This 90-minute long workshop will cover an introduction to the open source Frictionless Data tools. Participants will learn about data wrangling, including how to document metadata, package data into a datapackage, write a schema to describe data and validate data. The workshop is suitable for beginners and those looking to learn more about using Frictionless Data. It will be presented in English, but you can ask questions in English or Spanish.
Everyone is welcome to join, but you must register to attend using this link.
The fellows programme is part of the Frictionless Data for Reproducible Research project overseen by the 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.
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. This workshop will be led by the members of the first cohort of the fellows programme: Lily Zhao, Daniel Ouso, Monica Granados, and Selene Yang. You can read more about their work during this programme here: http://fellows.frictionlessdata.io/blog/.
Additionally, applications are now open for the second cohort of fellows. Read more about applying here: https://blog.okfn.org/2020/04/27/apply-now-to-become-a-frictionless-data-reproducible-research-fellow/
Lilly is the Product Manager for the Frictionless Data for Reproducible Research project. She has her PhD in neuroscience from Oregon Health and Science University, where she researched brain injury in fruit flies and became an advocate for open science and open data. Lilly believes that the future of research is open, and is using Frictionless Data tooling within the researcher community to make science more reproducible.