- How might we assure that IFRC’s data practices and policies ‘do no harm’?
- How might we collect and hold data responsibly and ethically?
A suggested step by step process to achieve learning objectives.
- Begin with Data Monologues [SessionPlan 4] to surface experience amongst your participants.
- Run the Wheel of Data Misfortune [Exercise 4] to deepen awareness of data protection issues.
- Use The Need to Develop a Data Protection Framework [SlideDeck 10] to provide a case study and more information.
- Use the Data Simulation [SessionPlan 3] to simulate data-workflows using the Data Responsibility Scenario [Exercise 5].
- End with participants filling out the Data and Technology [Checklist 1] to determine an efficient and legitimate data workflow in their own projects.
- Distribute the Data Responsibility Policy [Handout 4] to give participants a template for creating a policy in their own organisation.
Pick and choose ingredients to create your own recipe. Do you have an ingredient we’re missing? Send an email to email@example.com.
Short, discrete social learning experiences
- Wheel of Data Misfortune [Exercise 4]. An interactive way for groups to share responsible data stories.
- IDP Data Responsibility Scenario [Exercise 5]. Poses a problem set around an International NGO in Ethiopia that supports internationally displaced persons.
- PMER Data Simulation [Exercise 9]. Uses an example emergency to guide conversations on risks and data protection
Longer social learning experiences
- Data Simulation [SessionPlan 3]. To ‘simulate’ data workflows for various topics where data protection and responsibility will need to be applied.
- Data Monologues [SessionPlan 4]. Participants share a ‘data project lesson’ or ‘data fail’ to help talk about Responsible Data Use and Data Protection Guidelines.
Distilled information for use as standalone or parts of presentations
- Data and Technology Checklist [Checklist 1]. A basic checklist on technology and data processing in software projects to develop an efficient and legitimate data workflow.
ODK and Data Protection [Checklist 2]. For mitigating risks when using the Open Data Kit.
- Data Hygiene [Checklist 3]. Types of data to consider when assessing data protection needs
For documentation of essential elements of the learning experience
- The Need to Develop a Data Protection Framework [SlideDeck 10]. Examines data management and protection during an outbreak.
- Data Responsibility Roadmap [SlideDeck 16]. How 510 approached GDPR and efforts to address their data responsibities.
- Data Protection Conversation [SlideDeck 17] Learnings from efforts to improve data protection measures at IFRC.
To be distributed to participants for use post-training
- Responsible Data Guidance [Handout 2]. Covers key concepts and definitions. Also contains a dataset checklist and a data analysis checklist.
- IFRC Data Protection FAQ’s 2018 [Handout 3]. To aid IFRC staff plan and prioritise next steps for data protection.
- Data Responsibility Policy [Handout 4]. A template for creating an organisational policy. Created by 510, an Initiative of the Netherlands Red Cross.
- People Before Data [Handout 11]. A drawing about data metrics.
- Polio Monitoring Simulation [Handout 13]. How will you safeguard data during a polio outbreak?
Other relevant modules from the data playbook beta:
Further reading resources:
- Glossary: Consider building a glossary of terms for your learners.
- Responsible Data Forum. Hub for Responsible Data Practitioners
- Handbook on Data Protection in Humanitarian Response. Tool to raise awareness and assist humanitarian organizations in complying with personal data protection standards. ICRC and Brussels Privacy Hub.