Principles We adhere to:
- Design so that impact can be measured continuously and incrementally, focusing on outcomes, not just outputs. programs
- Make use of existing data, including open data sets and data from interoperable systems.
- Use rigorous data collection methods. Consider and address potential biases and gaps in the data collected, perform data quality checks, and maintain strong documentation behind collected data.
- Close knowledge gaps by contributing data to the development community and using data and interoperability standards.
- Use quality real-time or timely data to support rapid decision making, improve programming for users and inform strategy.
- Present data in formats that are easy to interpret and act on, such as data visualizations.
- Create a data use culture by prioritizing capacity building and data use efforts across all stakeholder groups, including the groups whose data are being collected.
- Be holistic about data collection and analysis. Collect data from multiple sources, and use a mix of data collection and analysis methods. Analyze your data collaboratively with stakeholders.
- Identify and use open data and interoperability standards.
Collect and use data responsibly according to international norms and standards