Summary and Schedule

This lesson provides an introduction to digital research sustainability. Digital research practices involve a number of activities that can lead to carbon emissions. This lesson is designed to identify such activities and provide practical ways to reduce the emissions.

We will use case studies to explore the carbon impact of digital research activities in four different contexts. Each case study will include some action items that can be implemented to reduce the associated emissions.

After completing this lesson, you should be able to:

• Explain the big picture for reducing carbon emissions and how that applies to digital research
• Understand the difference between energy and power, how energy is produced, what are low-carbon energy sources and how they operate
• Explain what embodied carbon is
• Use the greenhouse gas (GHG) protocol to estimate carbon emissions
• Identify which aspects of a research workflow are most carbon‑intensive and why
• Explore ways to measure and estimate carbon emissions from research software development
• Identify tools and resources to help estimate emissions associated with daily computational research tasks
• Explore ways to measure and estimate carbon emissions from High Performance Computing clusters

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Target Audience

This lesson will be of interest to a wide range of audience, including:

• Researchers who write code
• Research Software Engineers who support researchers
• Lab scientists who do computational work
• Researchers who use HPC
• Researchers who use GPUs

By attending this course, you will be able to better understand the carbon impact of your digital research activities and potential ways to reduce that impact. No prior knowledge of digital research sustainability is required.

The materials in this lesson are inspired from the Green Software Foundation courses and the Green DiSC Digital Sustainability Certification.

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Green DiSC Digital Sustainability Certification

Green DiSC is the first open-access certification scheme which provides a roadmap for research groups, computing teams, and institutions who want to reduce the environmental impacts of their computing activities.

More details: https://www.software.ac.uk/GreenDiSC

Development of this training material has been supported by Research England Research Culture funding provided through Imperial College London.

This lesson is built with The Carpentries Workbench.

	Setup Instructions	Download files required for the lesson
Duration: 00h 00m	1. Why sustainable digital research matters	What are the net zero goals and why are they important for addressing climate change? How does digital research contribute to greenhouse gas emissions, and what is the scale of this contribution? What is mindful computing and how can it be applied to reduce carbon emissions in research? Why is it important for researchers to consider the environmental impact of their digital activities?
Duration: 00h 20m	2. Energy, power and carbon	What is the difference between energy and power, and how are they measured? How does carbon intensity of electricity vary throughout the day and year, and what causes this variation? What is the difference between embodied carbon and operational carbon emissions? How does the Greenhouse Gas (GHG) Protocol categorize different types of emissions?
Duration: 01h 00m	3. Digital research activities with sustainability issues	What are the main sources of carbon emissions from computers, storage devices, and data centres? How do embodied and operational emissions compare for different types of hardware and storage technologies? What factors influence whether data centre computing is more or less carbon intensive than local computing? How can research data management practices and computational services contribute to carbon emissions?
Duration: 02h 00m	4. Introduction to the Case Studies	How these sources of carbon emissions map to specific research roles? What can they do to mitigate their carbon footprint, in concrete terms?
Duration: 02h 05m	5. Case Study 1 - Research Software Engineer	What are the main sources of carbon emissions in research software development and deployment? How can a Research Software Engineer measure and estimate emissions from software development, CI/CD workflows, LLM usage, and software execution? What strategies can reduce carbon emissions from widely-used research software? How do emissions from software usage compare to emissions from software development?
Duration: 02h 35m	6. Case Study 2 - Lab Scientist doing computational work	What are the main carbon emission sources for a researcher conducting computational data analysis? How do data storage choices impact long-term carbon emissions in research projects? What are the trade-offs between using different LLM models for generating research code? How can hybrid storage strategies reduce carbon emissions while maintaining data accessibility?
Duration: 02h 49m	7. Case Study 3 - HPC User	What are the key sources of carbon emissions when using High Performance Computing facilities? How can HPC users estimate emissions when clusters provide different levels of carbon monitoring tools? What strategies can reduce carbon emissions from HPC workloads without compromising research throughput? How do workload optimization, resource selection, and job management affect carbon emissions?
Duration: 03h 19m	8. Case Study 4 - GPU Computing User	What are the sustainability considerations related to using heterogeneous computing architectures, including graphical processing units (GPU), tensor cores and other alternative hardware? What are the practical implications for their use in machine learning and general single instruction multiple data (SIMD) computations?
Duration: 03h 49m	9. Summary	What are the key concepts and strategies covered in this course for reducing carbon emissions in digital research? How can the measurement and estimation methodologies learned in this course be applied to your own research? What are the most impactful changes you can make to reduce emissions in your specific research context?
Duration: 04h 09m	Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

FIXME: Setup instructions live in this document. Please specify the tools and the data sets the Learner needs to have installed.