Title: Ten simple rules to make your computing more environmentally sustainable
There is little doubt that data science will be a key tool to tackle climate change, but we often forget to consider how our own work also contributes to the problem. The infrastructure we use and the algorithms and code that we write and run all consume large quantities of electricity, whose production is responsible for significant GHG emissions.
Details
Description:There is little doubt that data science will be a key tool to tackle climate change, but we often forget to consider how our own work also contributes to the problem. The infrastructure we use and the algorithms and code that we write and run all consume large quantities of electricity, whose production is responsible for significant GHG emissions.
Subject Area: 1. Natural sciences – Computer and information sciences
Education Level: Higher education
Education Use: Professional development
Author: Loïc Lannelongue, Jason Grealey, Alex Bateman, Michael Inouye Date added: 26-02-2022Language: EN
Publisher/Institution: PLOS COMPUTATIONAL BIOLOGY
License type: Creative Commons-Attribution (CC BY) 
Primary User: Teacher
Learning resource type (IEEE LOM): Narrative Text (theory)
Technical type (IEEE LOM): Text – Document
Time to read: 120min
Learning outcomes:
- Have a general understanding of Carbon Footprint
- Create a list of equipment to be checked
- Acquire data relating to the consumption of the equipment present
- Evaluate the carbon footprint of devices’ production
- Create a list of services to be checked
- Evaluate the energy consumption of digital services in use
DigComp competence area: 4. Safety – 4.4 Protecting the environment
DigComp proficiency level: 4.Tasks, and well defined and non-routine problems
Link: https://doi.org/10.1371/journal.pcbi.1009324
Key words: carbon footprint, code efficiency, minimization of electronic waste