March 3, 2026Open Access

SORS: enhancing FAIRness in Harvard dataverse with variable-level metadata and differential privacy

Key Points

Integration of differential privacy techniques enhances data access while maintaining confidentiality, supporting fair data practices.
Variable-level metadata support extends beyond tabular formats, incorporating multiple schemas for improved discoverability.
The Dataverse Project enhances interoperability of datasets, making them easier to connect and use in various applications.
A focus on compliance with FAIR principles ensures broader accessibility and responsible data management.

Abstract

We highlight recent advances in the Dataverse Project aimed at extending support for variable-level metadata beyond tabular data, incorporating DDI, CDI-DDI, CroissantML, and other schemas to enhance discoverability and interoperability. Additionally, we explore the integration of differential privacy techniques to improve access to sensitive data while maintaining confidentiality, thereby promoting broader accessibility and compliance with FAIR principles.

SORS: enhancing FAIRness in Harvard dataverse with variable-level metadata and differential privacy

Key Points

Abstract

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