Module Aim & Introduction
This module helps you plan, collect, and manage sustainability data so it is accurate, traceable, and ready for reporting.
You will:
And maintain an evidence‑ready audit trail.
Map sources and owners,
Design capture tools with validation,
Apply data‑quality controls,
Protect privacy,
Learning Outcomes
Knowledge
- Data governance & quality;
- EU data infrastructures (e.g., INSPIRE);
- Ethics & privacy (e.g., GDPR);
- Documentation & metadata best practice.
Skills
- Clean and preprocess environmental datasets;
- Use open‑source tools (e.g., R/Python) to visualise indicators;
- Implement validation for integrity and consistency;
- Develop reproducible workflows with version control.
Autonomy & Responsibility
- Design transparent data‑collection plans;
- Evaluate ethical issues;
- Champion data‑quality processes across teams.
Jargon Buster
- Data Dictionary: Register of each metric (definition, unit, owner, source, frequency).
- RACI Roles: Responsible, Accountable, Consulted, Informed.
- Primary vs Secondary Data: Collected directly vs sourced from others.
- Validation: Rules that prevent or flag bad inputs.
- Audit Trail: Evidence of where data came from and how it changed.
- Metadata: Information describing your data, so others can understand and reuse it.
