A safe, productive, non-judgemental environment where everyone is enabled to contribute to the best of their abilities and circumstances.
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Respect - Treat each team member with respect and dignity, appreciating diverse backgrounds and experiences.
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Inclusivity - Promote an inclusive environment where every member feels welcomed, valued, and safe to contribute.
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Integrity - Act honestly and ethically in all project activities and communications.
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Excellence - Strive for excellence through persistence, grit, and continuous improvement.
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Accountability - Take personal responsibility for project work, communication and conducting ourselves ethically.
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Collaboration - Work together effectively by openly sharing ideas, providing support, and valuing all contributions.
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Communication - Communicate regularly through meetings, written channels, and informal discussions to stay aligned. Respond promptly to requests.
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Consensus - Make project decisions through constructive discussion leading to consensus while considering diverse viewpoints.
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Continuous learning - Commit to continuously developing skills, knowledge, and capabilities throughout the project.
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Impact - Have a positive impact on end users and stakeholders through adding value and advancing knowledge. Seek root causes and fundamental solutions over temporary symptom relief.
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Agile - Deliver work in short sprints with regular review, iteration, and adaptation based on feedback.
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Project Management - Maintain a prioritised backlog, user stories and release plan to focus efforts.
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Pair programming - where possible, collaborate in pairs to increase skills, accelerate progress, and improve code quality.
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Code review - Review code together to share knowledge, identify improvements, and fix defects.
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Testing - Verify code correctness through unit, integration and user testing.
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Version control - Use Git and GitHub for source control, collaboration, and release management.
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Conflict resolution - Address disagreements promptly via open discussion, adhering to values
- Planning - Focused on plan to deliver objectives (no solutionising!)
- Review – Focused on reviewing completed work in preparation for planning.
- Regular catchups – Focused on aligning status, progress, surfacing blockers.
- Retrospective – Optional, occasional, to review methods, offer feedback, suggest adjustments, etc.
- Conflict resolution - Address disagreements promptly via open discussion, adhering to values
Aim to collect, manage, use and share data in an ethical, reproducible and socially beneficial manner.
- Ethical Collection - Collect data in an ethical manner with informed consent. Avoid collecting illegal, unethical, or harmful data.
- Original Copies - Retain original, raw copies of data as collected without any processing or transformations applied.
- Privacy & Confidentiality - Protect personal and sensitive data through encryption, access controls, and aggregation/anonymisation. Follow laws and regulations like GDPR.
- Provenance & Documentation- Document data sources and origins. Track data lineage and processing steps. Record methodology, caveats, definitions.
- Common Standards & Terms - Use agreed common data standards and terminology to enable interoperability.
- Data Definitions - Clearly define data elements and adhere to those definitions across uses.
- Naming Conventions - Follow consistent naming conventions for files, folders, variables, and databases.
- Metadata - Assign descriptive metadata to document and enable discovery of datasets.
- Openness & Sharing - Make collected data open and shareable whenever possible. Avoid proprietary restrictions.
- Reproducibility - Enable others to reproduce results by sharing code, data, environment configurations and methodology.
- Version Control - Manage changes to data sources in a version control system like Git. Maintain history.
- Quality - Assess and ensure high quality complete data. Flag uncertainties, incomplete data, or errors discovered.
- Curation & Preservation - Curate data for long-term access and preservation. Use standard durable file formats and media.
- Citation & Credit - Require those using our data to cite the source and credit data creators. Cite sources appropriately.
- Minimising Bias - Identify and mitigate sources of bias in data collection, analysis, and inferences drawn.
- Responsible Use - Data should only be used for purposes consistent with ethical collection and for social good.
- Shared workspace: Microsoft Teams
- Communication: Microsoft Teams, WhatsApp
- Task management: Planner / Trello
- Code hosting: Github, Gitlab
- Version control: Git
- Data analysis: Python, R, Excel, PowerBI
- Documentation: Jupyter, Quarto, Markdown
- Referencing: Zotero