Figure 4: Checklist to ensure that data collection, analysis and storage is ethical Do no harm Ensure participants, particularly those who experience gender-based human rights violations, can be heard and are protected from harm during and after the data process. Apply ethical considerations such as: • Equality of access • Freedom to participate • Duty of care, ensuring no-one is hurt by taking part in the Gender Audit • Respect and integrity • Disclosure, privacy and confidentiality Recognise the sovereignty of the data including: • How it is generated • Who it is about • Who has permission to use it • Laws about where it is stored and accessed Be aware of unintentional bias, including gender bias. Be transparent about intentional biases and why you are adopting them by asking: • Whose voices may be silenced or ignored? • What considerations impact on the data? • What are the lenses through which data is analysed? Understand the contexts from which the data is gathered, assess any risks and match data gathering activities to context, participants/stakeholders and resource constraints. Ensure reliability Disaggregate data against cross-cutting factors (e.g. disability, sex, age, ethnicity etc). Validate findings with the participants/people about whom data is being collected. Make sure your recommendations are based on reliable information. Link conclusions to the context within which the data was gathered. Acknowledge any limitations in the data gathered. Ensure data (both primary and secondary) is referenced appropriately. 16