News

An update on the CS&S 4-day workweek trial

Nov 15, 2023

After 3 months, we surveyed staff and fiscally sponsored projects to surface impacts, challenges and learnings from the trial, and found unanimous support for a continuation of the 4-day workweek on the CS&S core team. 

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Aug 21, 2023

Inside the Culturally Responsive Education in Environmental Data Science (CREEDS) Workshop

Dr. Natasha Gownaris (Tasha), an Assistant Professor at Gettysburg College, describes a student-centered process for developing culturally responsive data science modules. This project was embedded in a larger initiative that brought together educators, practitioners, and community leaders to discuss how to make data science education more culturally responsive.

Jul 27, 2023

Lessons Learned from Organizing Data Science by Design Virtual Events

Data Science by Design (DSxD) is a community dedicated to developing a more open, ethical, and inclusive future for the field of data science. In this post, they reflect on lessons learned from organizing their virtual events.

Jun 21, 2023

CS&S to Trial a 4-Day Work Week

Aligned with our commitment to developing sustainable and data-driven practices that are in line with our values, CS&S is trialing a 4 day work week starting July 1, 2023.

May 12, 2023

Behind the Scenes: What it takes to run Pathways to Open Science

Event Fund supports more inclusive and accessible events in data science in order to lower barriers to participation in science and facilitate new collaborative relationships. Part of supporting emerging data science leaders to run good data science events includes developing a knowledge base for what it takes to run outstanding and creative events. In this post – part of an ongoing series that focuses on the organizing processes, tools, and practices used to run successful Event Fund-sponsored Open Science events – we learn about Openscapes and how their Pathways to Open Science program developed. Through this blog series, Event Fund seeks to highlight the processes and practices that undergird more inclusive and accessible data science event programming.

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