SSHOC D8.2 Certification plan for SSHOC repositories
Bibliographic record
Abstract
This report is the first deliverable of Task 8.2 “Trust & Quality Assurance” within WP8 of the SSHOC project. The distributed character of data infrastructures within the SSHOC communities requires developing an agreed approach to assessing the trustworthiness and quality of data repositories. This deliverable provides an overview of Trusted Digital Repository (TDR) standards offering a certification framework for communities represented in the SSHOC project (CESSDA, CLARIN, DARIAH, E-RIHS). Moreover, the deliverable lays the ground for the SSHOC trust work that is needed in order to facilitate the adoption of TDR standards and the FAIR principles in SSH data repositories across the board. In this report, ‘trust’ refers to the landscape of issues, standards and processes related to trustworthy digital repositories. Trust between all parties in the quality of data and services is critical for research infrastructure in terms of people, processes and technologies. The level of trustworthiness can be assessed through evaluation against agreed requirements. The SSHOC project unites 20 partner organisations and a further 25 linked third parties. When this report refers to the SSHOC repositories, it means the research data repositories within CESSDA ERIC, CLARIN ERIC, DARIAH ERIC and E-RIHS communities regardless of their participation in the SSHOC project. It is also important to note that in the context of this report, the term ‘quality’ refers to the technical quality of the repositories i.e. their compliance with the Trusted Digital Repository standards, not to the scientific quality of their digital assets. In line with the aims of Task 8.2, the report specifies modes of support in building trust and helping repositories reach TDR certification. The report charts the current trust landscape within the SSHOC communities and selects the repositories that will be the main focus of the support activities provided by Task 8.2 at later stages in the project. In addition, the report outlines a certification plan for these repositories. All repositories within the SSHOC communities are potential recipients of support from Task 8.2, but the efforts must be aligned with realistic expectations of progress during the project timeframe. CoreTrustSeal is selected as the standard TDR certification reference within the task. Due to the diversity of repositories within the SSHOC communities, a flexible yet sustainable approach to trust is needed that is adaptable to a wide variety of data infrastructures. The CoreTrustSeal provides a demonstrable approach to internal and external review, providing a means to determine the strengths and weaknesses of data stewards and a basis for comparison between them. However, certain types of organisations for which the CoreTrustSeal requirements are not applicable are also identified. Task 8.2 helps identify these cases and thus develop the CoreTrustSeal framework to better support a variety of repositories. Further work for Task 8.2 includes the provision of recommendations for sustainably maintaining trust across the SSH ERICs beyond the lifetime of the SSHOC project. This document is relevant to the SSH ERICs and to repositories across the SSHOC communities. There are no direct dependencies with other SSHOC tasks, but Task 8.2 aligns itself as necessary with both SSHOC tasks and existing EOSC-related efforts promoting trust and the FAIR principles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.043 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".