CHECKLIST: ENSURE DATA COLLECTION, ANALYSIS AND STORAGE IS ETHICAL5 Do no harm Base the data process on international human rights standards of participation, non-discrimination, inclusion and equality. Ensure participants, particularly those who experience 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 MEAL, • respect and integrity, • disclosure, privacy and confidentiality. Recognise the sovereignty of data (the idea that data is subject to laws and governance structures within the nation it is collected) 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 human rights standards, include cross-cutting factors (such as gender, disability) as appropriate to your outcomes. Validate findings with people on whom data is being collected. Make conclusions 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. 23