As the autumn leaves turn red and yellow 🍂🍁, we cozy up here in Switzerland to kick off our first data science course of the openwashdata academy. Big shout out to you from all over the world who have joined us! We also co-hosted at UNC Water and Health Conference the session on Data: A Key to Unlocking Quality in WASH Programmes where we advocated and discussed the future of open data in WASH!
Highlights
🏆 80+ countries, 120+ attendees, and 200+ registrations: A successful kick-off of Data Science for openwashdata!
On 31st of October, our first edition of the Data Science for openwashdata course started.
With more than 200 registrations from all over the world, our first module, spanning two and a half hours, witnessed an astounding 120+ participants brimming with enthusiasm and curiosity.
Our first cohort is diverse and covers more than 80 countries with many participants from the global south. Last week, we delved into the basics of open data tools such as the Quarto documenting system, version control and GitHub, R programming and more journeys await ahead. The successful kick-off has left us more thrilled, excited, and motivated to steer this academy on a path of continuous growth and learning.
Eager to be part of this course? Join us for next edition! Sign up for the course today: https://docs.google.com/forms/d/e/1FAIpQLSdYs9WIZuO7_2ERqUYdrgbNAdq0M5zjssCmgXi7UiL3Mlf5Qg/viewform
🔢 New datasets! Two datasets (UPGro project) about water pumps are released.
We developed two new R data packages from the data collected part of the project UPGro (Unlocking the Potential of Groundwater for the Poor). The raw data was already publicly available archived online.
The first data package waterpumpkwale is for monitoring weekly volume of hand pumps in Kwale, Kenya with records in year 2014 and 2015. The second data package grdwtrsmpkwale is for research and planning of water and solid waste management in Kwale, Kenya, containing water analysis data collected in 2016.
waterpumpkwale: https://openwashdata.github.io/grdwtrsmpkwale/grdwtrsmpkwale: https://openwashdata.github.io/waterpumpkwale/
An illustration of weekly volume change of some water pumps sorted by their total annual volume from top to bottom. Grey areas mean no volume data available.
Get Involved
We truly believe that openwashdata project prospers when we have YOU work together and promote open science and data practice! No matter what background you are from, we come up with some ways for you to get involved:
- Join our chatroom to meet people!
- Share your WASH data with us
- Spread the word. Forward this email.
- Got more ideas? Leave us a message on Matrix to collaborate!