- 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.
Download the module description (PDF) or download all the resources contained in this module here.