Digital Repository Interoperability: Design, Implementation and Deployment of the ECL Protocol and Connecting
Bibliographic record
Abstract
This paper describes the design and implementation of the eduSource Communication Layer (ECL) protocol. ECL is one outcome of a pan-Canadian project called eduSource Canada to build an open network of interoperable digital repositories. The design goal was to achieve a highly flexible, easy-to-use, and platform independent communication layer protocol that allows new and existing repositories to communicate and share resources across a network. ECL conforms to IMS Digital Repository Interoperability (DRI) specifications and supports four main functions: search/expose, submit/store, gather/expose and request/deliver. The ECL protocol builds on the latest standards and is flexible with respect to metadata schemas and repository contents. To support easy adoption of the protocol we provide middleware components for connecting existing systems. The ECL is currently used in the eduSource network, and we have begun work bridging with other interoperable initiatives such as Open Knowledge Initiative (OKI). Based on our experience, ECL is truly flexible and easy to use.
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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 | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".