Conceptual framework on the implementation of workflows concerning appraisal, reappraisal, retention and preservation of digital objects: Retention (Re) Appraisal - Iteration Logic (RRAIL)

This document proposes an approach to the logical choices, including assessments and interventions, that must be iterated over time to ensure the correct digital objects are appropriately retained and maintained. Effective digital object appraisal, retention and reappraisal are fundamental to maintaining a reliable research data infrastructure. The workflows presented here may be implemented by a variety of stakeholders such as repositories, archives, and other research data management service providers and are relevant to research data support staff such as data stewards and data curators. Aligned with the EOSC Long-Term Data Retention (LTDR) Task Force’s Terms of Reference; this paper on, Retention, (Re) Appraisal - Iteration Logic (RRAIL), draws on key work from the EOSC EDEN project (e.g., Core Preservation Processes), the FIDELIS project (e.g., Transparent Trustworthy Attributes Matrix - TTRAM), and the CoreTrustSeal Levels of Retention, Curation and Preservation (LoRCAP). These inputs help define repository characteristics and the metadata required to communicate different levels of care. Together, this document provides a coherent model for improving decision-making, transparency, and long-term management of digital objects across the EOSC ecosystem.

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Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-26
DOI
https://doi.org/10.5281/zenodo.19231270
Primary Topic
Research Data Management Practices
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article
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article

Conceptual framework on the implementation of workflows concerning appraisal, reappraisal, retention and preservation of digital objects: Retention (Re) Appraisal - Iteration Logic (RRAIL)

Hervé l'Hours, Micky Lindlar, Jacques Flores-Dourojeanni
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Conceptual framework on the implementation of workflows concerning appraisal, reappraisal, retention and preservation of digital objects: Retention (Re) Appraisal - Iteration Logic (RRAIL)

Hervé l'Hours, Micky Lindlar, Jacques Flores-Dourojeanni
article en

Abstract

This document proposes an approach to the logical choices, including assessments and interventions, that must be iterated over time to ensure the correct digital objects are appropriately retained and maintained. Effective digital object appraisal, retention and reappraisal are fundamental to maintaining a reliable research data infrastructure. The workflows presented here may be implemented by a variety of stakeholders such as repositories, archives, and other research data management service providers and are relevant to research data support staff such as data stewards and data curators. Aligned with the EOSC Long-Term Data Retention (LTDR) Task Force’s Terms of Reference; this paper on, Retention, (Re) Appraisal - Iteration Logic (RRAIL), draws on key work from the EOSC EDEN project (e.g., Core Preservation Processes), the FIDELIS project (e.g., Transparent Trustworthy Attributes Matrix - TTRAM), and the CoreTrustSeal Levels of Retention, Curation and Preservation (LoRCAP). These inputs help define repository characteristics and the metadata required to communicate different levels of care. Together, this document provides a coherent model for improving decision-making, transparency, and long-term management of digital objects across the EOSC ecosystem.

Zenodo (CERN European Organization for Nuclear Research)
University of Essex (GB), Utrecht University (NL), Technische Informationsbibliothek (TIB) (DE), UK Data Archive (GB), UK Data Service (GB)
Openalex Percentile: Top 7%
Research Data Management Practices
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Conceptual framework on the implementation of workflows concerning appraisal, reappraisal, retention and preservation of digital objects: Retention (Re) Appraisal - Iteration Logic (RRAIL) — Hervé l'Hours, Micky Lindlar, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS