Masking School
Building digital competence in privacy-aware audiovisual data management. Join our comprehensive training programs designed for SSH researchers and data stewards.
Learning Paths
For Researchers
Learn to de-identify audiovisual data, extract behavioral features, and integrate masking into research workflows.
- Introduction to Masking (1.5h)
- Hands-on Workshop (4h)
- Summer/Winter School (3 days)
For Data Stewards
Develop expertise in data governance, GDPR compliance, and supporting researchers with privacy-aware data management.
- Data Governance Fundamentals (4h)
- Masking Lab Co-creation (8h)
- Train-the-Trainer Workshop
For Developers
Contribute to the SYNAPSIS platform, develop new masking algorithms, and build custom integrations.
- Platform Architecture (2h)
- API Integration Workshop (4h)
- Maskathon Hackathon (2 days)
Certification Exploration
We are exploring what a future certification pathway for privacy-aware audiovisual data management could look like.
Future Certification
Under Development
What We're Exploring:
- Competency frameworks for AV data masking
- Assessment criteria and learning outcomes
- Integration with existing data stewardship pathways
- Community input on certification needs
Not Sure Where to Start?
Take our quick assessment to find the right learning path for your role and experience level.
Course Catalog
Introduction to Masking
Fundamentals of audiovisual data de-identification, privacy principles, and MaskAnyone toolkit overview.
Hands-on Workshop
Practical training with real datasets. Upload, configure, process, and archive masked audiovisual data.
Summer/Winter School
Intensive 3-day program covering advanced masking techniques, ethics, FAIR principles, and collaborative workflows.
What You'll Learn
Core Topics
- Privacy principles and GDPR compliance
- MaskAnyone toolkit features and customization
- Face de-identification methods and evaluation
- Voice anonymization and prosody preservation
- Body movement tracking and behavioral extraction
Practical Skills
- Uploading and managing data securely
- Selecting appropriate masking methods
- Quality control and verification
- Metadata creation and FAIR archiving with DANS
- Informed consent templates and ethical workflows
Special Events
Masking Lab
A co-creation forum bringing together extensive users, data stewards, ethics officers, and infrastructure partners to address advanced challenges.
Focus Areas:
Ethics & Compliance
GDPR, informed consent, IRB considerations
FAIR Principles
Metadata standards, findability, accessibility
Maskathon
A hackathon-style collaborative event for developers, data stewards, and computer scientists to advance masking technology.
Challenge Tracks:
- Algorithm Development
- Benchmark & Metrics
- Platform Integration
- Training Materials
Event Calendar 2026-2027
Past Events
SURF Research Bootcamp 2025
MaskAnyone hands-on workshop at Radboudumc Nijmegen
Event details →Upcoming Events
Introduction to Masking Workshop
1.5-hour introduction for PIs and support staff
Hands-on Data Masking Workshop
4-hour practical session for ECRs and data stewards
Masking Lab Co-Creation Forum
Full-day workshop on ethics and FAIR principles
Masking School
Extensive hands-on training for researchers and data stewards
Pilot Demonstration
Platform demonstration and hands-on session
Maskathon Hackathon
2-day collaborative development event
Pilot Demonstration
Platform demonstration and hands-on session
SYNAPSIS Summer School
3-day intensive closing event
Registration Information
How to Register
- 1. Check event eligibility and prerequisites
- 2. Complete online registration form
- 3. Receive confirmation email with details
- 4. Attend event and receive attendance confirmation
Eligibility Requirements
- Affiliated with partner institution
- Active researcher or support staff
- Working with audiovisual data
- No technical expertise required
Scholarships Available
Fee waivers and travel scholarships available for participants from underfunded institutions.
Register for Training
Join the SYNAPSIS community and start your journey toward privacy-aware research excellence