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Accès ouvert déclaré 2026 article

Working Group on Trusted Research Environments for Sensitive Data (WG-TRESD)

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Objective: Through the Research Data Alliance, an international group of researchers has formed the Working Group on Trusted Research Environments for Sensitive Data (WG-TRESD). This group aims to produce a better understanding of the elements making up TREs, bridging terminology boundaries to ease the set-up and operations of TRESD. The Working Group seeks members who want to keep track of developments with TREs. Methods: The Working Group is focused on four problem areas. (1) There are no community-agreed technical blueprints that provide building blocks and adaptable infrastructure components for TRESD. This increases the complexity for anyone wanting to set-up a structure and makes existing TREs less comparable. (2) TREs lack interoperability to support code moving between TREs, working with data locally (similar to federated learning in machine learning settings). This makes cooperation between data controllers difficult. (3) Balancing risks of data disclosure and utility of the environment for researchers is an ongoing challenge. For informed decision making, a risk catalog would be helpful, with mechanisms specified to lower the exposure to a specific risk. (4) FAIR Research Data Management. Curating and sharing metadata about sensitive/confidential data is challenging. There is no well-understood process for determining what can be shared, and with whom. Results: We'll share the status of Working Group activities in each problem area, highlighting demonstration projects, writings, and international collaborations. Conclusion: We invite the IPDLN community to be follow and join WG-TRESD efforts to improve secure data use.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Working Group on Trusted Research Environments for Sensitive Data (WG-TRESD)
Date Crossref
06/07/2026
Éditeur
Swansea University
Type
journal-article

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Sujets associés

Research Data Management PracticesScientific Computing and Data ManagementPrivacy-Preserving Technologies in Data

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