1. Getting started with AI in research software

• Objective: build foundational understanding of AI in the context of research software.
• Suggested topics:
  • Brief literature overview (landmark papers + policy reports relevant to science)
  • Types of AI most relevant for research
  • Overview of commonly used AI tools/libraries in research
  • Where / how AI fits into the research software lifecycle

2.  Applications of AI in Research Software

• Objective: Showcase how AI is being used, specifically where it’s being used responsibly
• Suggested topics/approaches:
  • Case studies across domains (healthcare, climate, physics, social sciences)
  • Different applications of AI: data analysis, simulation, design, and automation
  • Integration into reproducible workflows
  • Opportunities vs. hype: what AI does well and where it struggles

3. Creating and Evaluating data sets in AI

• Objective: Provide practical guidance for creating and evaluating data sets used in research software
• Suggested topics:
  • Documentation and metadata standards (FAIR principles)
  • Data curation, reproducibility practices
  • Sharing and licensing considerations

4. Responsible use of AI in research software

• Objective: Provide an overview of risks and considerations and guidance on how to responsibly use of AI in research software
• Suggested topics:
  • Risks & mitigation measures
  • Environmental/sustainable considerations
  • Practical guidance: documentation, transparency, open/reproducible practices

1. Green Computing: Introduction to Green Computing in Research

• Objective: understand why energy and resource sustainability matters in computational research, literature review
• Suggested topics:
  • What is green computing?
    • The carbon footprint of research software and data
    • Energy and other resources used
  • Overview of existing work - overview of relevant publications, community initiatives, guidelines, recommendations, policies
    • E.g. Green SIG within SocRSE, Green Algorithm, NetDRIVE, UKRI DRI Net Zero Scoping Project, Green Disc, etc.
  • The role of researchers and coders in reducing environmental impact
  • How to approach sustainable computing in practice
    • link to other guides in the series (if possible)

2. Green Computing: Writing Energy-Efficient Code

• Objective: understand different coding practices that reduce energy and resource usage.
• Suggested topics:
  • Choosing efficient algorithms and data structures
  • Profiling and optimising code performance
  • Avoiding wasteful patterns (e.g., busy-waiting, redundant loops)
  • Balancing code readability and efficiency
  • Tools for tracking and improving code energy impact (e.g., CodeCarbon, Green Algorithms)
    • Integrating footprint tracking into code or CI pipelines

3. Green Computing: Hardware-Conscious Programming

• Objective: understand techniques for sustainable use of cloud and HPC resources.
• Suggested topics:
  • Match code to appropriate hardware for sustainable execution - when to use CPUs vs. GPUs vs. cloud-based instances to minimize carbon impact when using large-scale computing platforms
  • Minimising overuse of high-performance resources
  • Understanding the energy cost of different cloud regions/providers
  • Efficient use of HPC and cloud services (batching, resource scaling, carbon-aware job scheduling (timing, location, low-carbon energy periods))
  • Tools to estimate and track job footprint

4. Green Computing: Green Data Practices

• Objective: understand how to reduce the footprint of data storage and movement.
• Suggested topics:
  • Efficient file formats and data compression/minimisation
  • Smart storage (e.g., tiered archiving, deduplication)
  • Reducing excessive data transfers
  • Caching, checkpointing, and avoiding duplicated runs
  • Data lifecycle management and disposal
  • Workflow automation and reproducible data pipelines (e.g., tools like Snakemake, Nextflow)
  • Sharing results and metadata for reuse

5. Green Computing: A Researcher’s Checklist for Green Computing

• Objective: Provide a practical summary and checklist for daily use and embedding sustainability into research practice
• Suggested topics:
  • Quick self-audit of your coding and computing practices
  • Checklist for project planning
  • Energy and resource sustainability in grant applications and reporting
  • Outreach, advocacy, and contributing to a low-carbon research culture

1. EDI Practices: Inclusive Event Planning From Start To Finish

• Objective: understand the key stages of event planning where inclusion should be considered, and apply frameworks for embedding EDI throughout the process.
• Suggested topics:
  • designing accessible and inclusive registration processes: structure registration forms to collect access needs respectfully and inclusively, while minimising barriers to participation
    creating a welcoming environment: codes of conduct and beyond
  • representation matters: inclusive speaker and panel selection: applying equitable criteria for selecting diverse speakers and panels and developing strategies for proactively inviting underrepresented voices
  • accommodating access needs for physical, virtual, and hybrid events: plan for a range of access requirements across different event formats, ensuring all attendees can participate fully
  • avoiding bias in call for proposals and review processes: design fair, anonymised, and bias-aware submission and review workflows
  • supporting participation: childcare, stipends, and travel grants: financial and logistical support mechanisms to reduce exclusion and broaden participation
  • timing and time zones: designing for global participation: scheduling and formats that accommodate international and geographically diverse audiences

2. EDI Practices: Fostering Inclusive Contribution Models in Open Projects

• Objective: recognise inclusive contribution pathways and adapt onboarding materials and workflows to reduce barriers.
• Suggested topics:
  • onboarding contributors from diverse backgrounds (welcoming contributors from non-traditional or underrepresented backgrounds)
  • language matters: writing inclusive and accessible documentation
  • creating a culture of respect: codes of conduct in practice
  • recognising and valuing non-code/non-content contributions as equality valuable
  • governance and decision-making structures that support equity and inclusion and mitigating bias in project decision-making and leadership
  • building inclusive maintenance and mentoring pathways for diverse contributors to grow into maintainers, mentors, or leaders

3. EDI Practices: Community Building That Promotes Belonging 

• Objective: define and communicate inclusive community values that foster a sense of belonging for all members.
• Suggested topics:
  • co-creation and participatory approaches to community growth that reflect diverse needs and voices
  • supporting marginalised voices in community spaces - structural and practical ways to recognise and uplift the voices of underrepresented members
  • designing accessible and actionable feedback mechanisms that support inclusion 
    and genuinely inform community development
  • conflict resolution and support structures for members
  • inclusive visual and narrative representation in community messaging and recognition of how imagery, language, and storytelling impact perceptions of belonging and representation

4. EDI Practices: Designing Inclusive and Culturally Responsive Training

• Objectives:  recognise and apply principles of universal design for learning and cultural responsiveness in training content development that that accommodates different physical, cognitive, and technological needs
• Suggested topics:
  • accessible training delivery: formats, tools, and materials
  • diversifying instructor teams and guest speakers to model inclusivity
  • creating safer learning environments
  • supporting different learning/cognitive styles and language needs with pedagogical strategies
  • using inclusive examples, case studies, and datasets that avoid stereotypes and reflect diverse realities
  • evaluating training with an inclusion lens - tools and approaches for evaluating whether your training is equitable, inclusive, and responsive to learners' needs.

Over the past year, we have been gathering community input, reviewing existing resources, and reflecting on where there are persistent gaps in guidance. From this process, we developed objectives and suggested topics for each new guide. These provide a framework for writers to work from, ensuring that the guides are structured, practical, and clearly connected to the challenges the community faces.

We look forward to working with contributors from across the research software community to create practical, accessible guidance that helps researchers embed AI, sustainability, and EDI into their research software practices.