Silvia Calamai
2026
Balancing FAIR and GDPR: A Governance Framework for Oral Archives
Elvira Mercatanti | Monica Monachini | Giovanni Abete | Silvia Calamai | Sergio Canazza | Alessandro Casellato | Virginia Niri | Cesarina Vecchia | Giulia Zitelli Conti | Giada Zuccolo
Proceedings of the Joint Workshop on Legal and Ethical Issues in Human Language Technologies and Computational Approaches to Language Data Pseudonymization, Anonymization, De-identification, and Data Privacy (LEGAL2026 and CALD-pseudo 2026) @ LREC 2026
Elvira Mercatanti | Monica Monachini | Giovanni Abete | Silvia Calamai | Sergio Canazza | Alessandro Casellato | Virginia Niri | Cesarina Vecchia | Giulia Zitelli Conti | Giada Zuccolo
Proceedings of the Joint Workshop on Legal and Ethical Issues in Human Language Technologies and Computational Approaches to Language Data Pseudonymization, Anonymization, De-identification, and Data Privacy (LEGAL2026 and CALD-pseudo 2026) @ LREC 2026
This paper presents a governance framework developed within the research project ROADS to support thesustainable management of oral archives, which constitute essential linguistic resources for interdisciplinary research and cultural heritage preservation. Oral archives raise complex ethical and legal challenges due to the hybrid nature of voice data, which function simultaneously as historical documents, scientific sources and biometric identifiers, thereby creating tensions between open science principles and data protection regulations. The proposed framework integrates FAIR principles (Findable, Accessible, Interoperable, Reusable) with Privacy by Design and the GDPR accountability principle through a multilayered approach. It introduces an access model that distinguishes between publicly available metadata and controlled access to identifiable audio materials, following trusted repository standards. The framework also incorporates consent management procedures and safeguards for legacy collections, enabling responsible data sharing while preserving scientific usability. More broadly, ROADS provides a transferable model to guide the transition from project-based archives to FAIR, sustainable and reusable research resources, ensuring compliance with data protection requirements and respect for the sensitivity of the documented contexts.
2020
A CLARIN Transcription Portal for Interview Data
Christoph Draxler | Henk van den Heuvel | Arjan van Hessen | Silvia Calamai | Louise Corti
Proceedings of the Twelfth Language Resources and Evaluation Conference
Christoph Draxler | Henk van den Heuvel | Arjan van Hessen | Silvia Calamai | Louise Corti
Proceedings of the Twelfth Language Resources and Evaluation Conference
In this paper we present a first version of a transcription portal for audio files based on automatic speech recognition (ASR) in various languages. The portal is implemented in the CLARIN resources research network and intended for use by non-technical scholars. We explain the background and interdisciplinary nature of interview data, the perks and quirks of using ASR for transcribing the audio in a research context, the dos and don’ts for optimal use of the portal, and future developments foreseen. The portal is promoted in a range of workshops, but there are a number of challenges that have to be met. These challenges concern privacy issues, ASR quality, and cost, amongst others.