Using our data to inform our work often means comparing, consolidating, and analyzing data. Data can be primarily sourced or used with secondary data sources. Data quality and standards are two key elements to become more data ready. This module is for practitioners who aim to improve data quality and advocate the use of data standards. This is a complex topic so it also aims to support those who question methodology and priorities in data workflows. Why do data standards matter and how might we address data quality issues?
- What are data standards?
- How might we improve data quality?
- What are some of the basics of survey design?
RECIPE
A suggested step by step process to achieve learning objectives.
- Start with Why Do Standards Matter [Exercise 11] to engage participants in the needs for standardization and quality.
- Discuss Opportunities and Barriers [Exercise 12] to help participants better understand the root cause of ‘data quality.
- Survey Basics [SlideDeck 22] gives an overview on how to build a survey to meet data standards.
- Consider how we might map Data Quality Workflows [SlideDeck 23]. What are some of the big questions and how might we map the workflows to inform our planning?
- Understanding Data Standards [SlideDeck 24] will help participants further refine their understanding of definitions and needs for data standards.
INGREDIENTS
Pick and choose ingredients to create your own recipe. Do you have an ingredient we’re missing? Send an email to data.literacy@ifrc.org.
Exercises
Short, discrete social learning experiences
- Why Do Standards Matter [Exercise 11] engages participants in the need for standardization and quality.
- Opportunities and Barriers [Exercise 12] helps participants better understand the root cause of ‘data quality.’
- Spreadsheet Test [Exercise 13] a “rawdata” worksheet, which represents fictitious beneficiary data previously gathered in villages that have been affected by a disaster.
Checklist
For documentation of essential elements of the learning experience.
- Counting People [Checklist 5] ensures that we are counting ‘people reached’ in a consistent way.
Slidedeck
Distilled information for use as standalone or parts of presentations.
- Survey Basics [SlideDeck 22] gives an overview on how to build a survey to meet data standards.
- How Data Quality Workflows [SlideDeck 23]. How might we map the workflows to inform our planning?
- Understanding Data Standards [SlideDeck 24] helps participants further refine their understanding of definitions and needs for data standards.
Handouts
Distilled information for use as standalone or parts of presentations.
- Example Data Validation Process [Handout 8] helps you plan your data validation strategy.
- Household Survey Scenario [Handout 9]. Role plays for use in a workshop.
Next Steps
Other modules within the playbook that have relevance to this module’s topic.
- Why should we share and collaborate on data? [Module 7]
- How can we protect and use data responsibly? [Module 4]
Further reading resources:
- Consider Christopher Kuner and Massimo Marelli, ICRC. Handbook on Data Protection in Humanitarian Action.
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