Sept 21, 18.00 CEST
Sept 22, 12.30 CEST
Policy makers and funders, researchers, research Infrastructures and research communities, repository managers, publishers and content providers
Interdisciplinary collaborations: Networks, services, methods
Legal aspects of open science; GDPR and IPR exploitation, RDM best practices
Training and skills for open science, Sustaining open science training: people, resources, governance
data anonymization, k-anonymity, km-anonymity
Amnesia is a flexible, user-friendly, free, and open-source data anonymization tool. Specifically, Amnesia transforms relational and transactional data to anonymized datasets where formal privacy guarantees hold by (1) removing direct identifiers (names, SSNs, etc.) and (2) transforming secondary identifiers (birth dates, zip codes, etc.).
The key idea regarding data anonymization is that identifying information is removed from the published data by presenting identifying information in an obscure or generalized way so that sensitive information cannot be connected to a person. Hence, a significant challenge is to provide the best trade-off between privacy guarantee strength and anonymized data quality. Amnesia supports k-anonymity and km-anonymity, two formal privacy guarantees which facilitate Open Access without compromising user privacy.
The Amnesia tool is available both as an online service and a local application focusing on enabling users to understand, tailor and guide the anonymization processes while exploring the quality of the anonymized data. The latest version of the tool (Amnesia 1.2.6) introduces a significant API upgrade comprising additional internal functions exposed as ReST services that allow more precise control on the anonymization engine (Amnesia API documentation link here).