FAIR & Frictionless workflows for tabular data | Online Workshop

4TU.ResearchData and Fric­tion­less Data have joined forces to orga­nize the work­shop “FAIR and Fric­tion­less Work­flows for Tab­u­lar Data”.

This online work­shop aims at intro­duc­ing researchers work­ing with tab­u­lar data with repro­ducible data work­flows, includ­ing how to make the data more FAIR and of high­er qual­i­ty. 

The par­tic­i­pants will learn how to use the Python Fric­tion­less Frame­work to cre­ate and edit meta­da­ta and schemas, how to val­i­date their data, and how to write a pipeline to pre­pare data for pub­li­ca­tion on 4TU.ResearchData.

The work­shop is a mix­ture of short lec­tures and hands-on live cod­ing (includ­ing exer­cis­es) using Jupyter note­books and an exam­ple dataset.

This hands-on work­shop will occur online over 2 half-day ses­sions on the 28 and 29 April from 12:30 — 17:00 hrs CET via Zoom.

Prerequisites

In order to join this work­shop you should know the basics of Python pro­gram­ming (e.g. pan­das, numpy pack­ages) and/or have com­plet­ed a Soft­ware Car­pen­try work­shop.

Programme

Thurs­day 28 April (Time zone CET)

Fri­day 29 April (Time zone CET)

12:30 — 13:00 — Instal­la­tion problems/questions 
13:00 — 13:10 — Wel­come 
13:10 — 13:25 — Brief recap 
13:25 — 14:30 — Val­i­date and Trans­form func­tions and Data pack­age 
14:30 — 14:45 — Break
14:45 — 16:15 — Val­i­date and Trans­form func­tions and Data pack­age 
16:15 — 16:25 — Break
16:25 — 16:50 — Data pub­li­ca­tion & 4TU.Researchdata
16:50 — 17:00 — Wrap up & clos­ing

Registrations

You can reg­is­ter for this work­shop online.

You will receive instruc­tions to install soft­ware and down­load the exam­ple datasets one week before the work­shop.

About the partners

Fric­tion­less Data is an open source project with­in the Open Knowl­edge Foun­da­tion (OKF), focus­ing on mak­ing research data more open, usable, and repro­ducible. 

4TU.ResearchData is an inter­na­tion­al data repos­i­to­ry for sci­ence, engi­neer­ing and design. Its ser­vices include cura­tion, shar­ing, long-term access and preser­va­tion of research datasets. These ser­vices are avail­able to any­one around the world. In addi­tion, 4TU.ResearchData also offers train­ing and resources to researchers to sup­port them in mak­ing research data find­able, acces­si­ble, inter­op­er­a­ble and repro­ducible (FAIR).

Authors: Lil­ly Win­free, Paula Mar­tinez Lavanchy