About Us

moirée — the name comes from the optical moire effect: when two fine grids are overlaid, new patterns suddenly emerge that were invisible in either individual image.

You know the phenomenon: a shirt with a fine stripe pattern flickers on television, two window grids overlap slightly, or you hold two sieves against each other — suddenly waves and circles appear that shouldn't be there and were previously invisible.

That is exactly what happens on this platform. On one side: lived experiences from professional life. On the other: scientific studies documenting structural disadvantage. Only when both are overlaid — when personal experience meets academic evidence — do patterns become visible that remain invisible in isolation. That is moirée.

"I've never seen a woman being disadvantaged in my industry. We're always very supportive!" — A well-intentioned sentence, spoken by a flatmate in 2026. No malice, no intent to trivialize. Simply an honest perception from a perspective in which certain patterns remain invisible. The obvious response would have been: show the data. But which data?

Research revealed a gap. EU reports from EPRA and Creative Europe exist as static PDFs — valuable, but not searchable, not filterable, not broken down to individual cases. American sources like the UCLA Hollywood Reports provide annual statistics but do not document individual experiences. In the DACH region, networks like the Digital Media Women organize events and mentoring — but no databases. Nobody collects anonymized individual cases and makes them searchable, filterable, and citable.

This gap is no coincidence. Individual experiences of professional disadvantage are difficult to capture: they are subjective, often subtle, and those affected have good reasons not to speak about them publicly. That is precisely why an infrastructure is needed that guarantees anonymity while enabling scientific citability.

moiree.eu is the answer to this gap: a platform that makes invisible patterns of professional disadvantage visible and citable — so that the statement "I've never seen anything like that" can in future be answered with structured, anonymized, searchable data. Launched in the DACH region, the platform is gradually expanding across Europe.

The core team is currently being assembled. moiree.eu was initiated by the moirée founders and is seeking collaborators from the fields of sociology, data science, UX design, and labor law.

We are particularly looking for:

• Researchers — with experience in qualitative social research, gender studies, or labor market research
• Developers — for frontend, data visualization, and accessible web development
• Legal experts — with expertise in labor law, anti-discrimination law, or data protection law (DACH + EU)
• Advisory board members — from academia, civil society, and the creative industries for the interdisciplinary scientific advisory board

If you are interested in contributing, please use the contact form further down on this page.

moiree.eu pursues one goal: making invisible patterns of professional disadvantage visible and citable. Not as a one-time report, but as a living, growing data infrastructure — open, transparent, and scientifically grounded. The vision is a Europe-wide platform where each country operates as an independent chapter — locally coordinated, culturally adapted, connected through a shared methodology and data architecture.

The entire project is Open Source:

• Source code under MIT License — freely available, modifiable, and reusable
• Data and content under Creative Commons CC BY 4.0 — freely usable with attribution

Why Open Source? Three reasons that also form the foundations of this project's eligibility for funding:

• Reproducibility: The entire codebase is forkable. An organization in France, Sweden, or Brazil can adopt the infrastructure and adapt it to their own context. No vendor lock-in, no dependency on a single team.
• Transparency: The methodology is publicly documented, the category definitions are academically grounded, and the limitations are clearly stated. Scientific credibility comes from traceability, not authority.
• Incrementality: moiree.eu is a living resource, not a one-time report. The database grows with every submission, the analysis becomes more precise with every new case.

You can find the complete source code on GitHub: github.com/moiree-eu

The platform's purple combines 51% pink — for the 51% of women in the world population — and 49% blue — for the 49% of men: color as a political statement.

Brand and Assets

The moirée logo is text-based and rendered as styled HTML text: moirée (moiree.eu). The project name is rendered as styled HTML text — there is no separate image file.

Primary color (accent): Purple #7A5AB5 (CSS variable: --primary) — used for statistics, highlights, and data visualizations.

Color palette: The design uses a muted, scientific color scheme with Purple (#7A5AB5) as the primary color, Teal (#2CA882), Coral (#D85A30), and Blue (#3B8AD4) as secondary colors. Light and dark modes are automatically supported.

Fonts: The project uses exclusively self-hosted open-source fonts — Playfair Display (headings), IBM Plex Mono (data and code), and Source Serif 4 (body text on editorial pages).

Journalists, NGOs, and researchers can find key statistics, citable graphics, and contact information on our press page.

Would you like to contribute, use the data, or have questions about the project? We look forward to hearing from you.