Ontologies of Synthetic Data
/01What is synthetic data, really? We probe what it means for data to be "real," "generated," or "made up," and how those distinctions shape knowledge claims.
WASP-HS Research Environment
Synthetic Data.
Synthetic Data.
Real Questions.
InterSynth Lab is an interdisciplinary research environment where social scientists and computer scientists investigate how synthetic data is made, represented, and trusted — and what that means for society.
4
Universities
7+
Researchers
5
Research themes
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Open questions
About
Interdisciplinary by design.
Synthetic data sits at the crossroads of computer science, social science, and the humanities. InterSynth Lab is built to live there — not above it.
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What is synthetic data?
Algorithmically generated data that imitates real-world distributions — used to train models, protect privacy, and fill gaps where real data is scarce or sensitive.
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Why does it matter?
Synthetic data is being deployed in healthcare, finance, and public administration today. The questions of bias, transparency, and accountability are urgent — not theoretical.
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Why interdisciplinary?
Generators are computational, but their consequences are social. We need both lenses — and the conversations between them.
Research
Five themes, one question.
What does it take for synthetic data to be trustworthy?
Bias, Representation & Intersectionality
/02Synthetic data inherits — and amplifies — the biases of the data and models that produce it. We study representation gaps and intersectional effects in generated datasets.
Intersectional Hallucinations
/03When generative models invent people, identities, or facts, who and what is being misrepresented? We map the systematic errors that fall along intersectional axes.
Verification & Transparency
/04We design frameworks for documenting, verifying, and auditing synthetic datasets so downstream users can trust what they are working with.
Synthetic Data in Society
/05From healthcare to public administration, synthetic data is being deployed at speed. We examine the practical, legal, and ethical stakes of those deployments.
People
Led by three PIs across three universities.
Francis Lee
Research Leader
Södertörn University
Lead investigator on the social and cultural dimensions of synthetic data and machine-learned knowledge.
Principal Investigator
Ericka Johnson
Research Leader
Linköping University
Co-PI investigating on the WASP-HS research environment exploring synthetic data, facts, representations, and transparency.
Principal Investigator
Ylva Söderfeldt
Research Leader
Uppsala University
Co-PI working at the intersection of history of ideas, medical knowledge, and synthetic data practices.
Principal Investigator
News
Latest from the lab.
Want to collaborate?
We welcome conversations with researchers, journalists, public-sector partners, and anyone working on or thinking about synthetic data.
Get in touch