How a Repository or Data Source Can Meet OpenAIRE and EOSC Interoperability Standards

To meet OpenAIRE and EOSC interoperability standards, a repository or data source needs to expose structured, EOSC-compliant metadata that OpenAIRE can aggregate and interconnect with other sources. OpenAIRE provides a dedicated validation service for exactly this purpose: it checks whether your repository or data source meets OpenAIRE and EOSC interoperability standards. The practical path is to (1) understand what "compliant metadata" means in practice, (2) prepare and expose that metadata, and (3) run the validation and fix what it flags. This guide is aimed at repository managers and infrastructure providers who need a concrete route from "we have a repository" to "we are interoperable."

What the validation service is for

OpenAIRE describes its infrastructure as supporting open access, data sharing, and scholarly communication, and it aggregates and interconnects content from repositories, CRIS systems, and journals with EOSC-compliant metadata. The interoperability validation service exists so that a repository or data source can confirm it produces metadata that fits this aggregation model.

Two things follow from that purpose:

• Validation is a conformance check, not a hosting service. It tells you whether your metadata can be consumed and linked by OpenAIRE and EOSC-compliant systems.
• The goal is interconnection. A compliant source does not just publish records; its records can be matched, deduplicated, and linked to publications, datasets, software, projects, and organizations elsewhere in the graph.

What EOSC-compliant metadata means in practice

OpenAIRE's own description of its aggregation work points to the core expectations. Metadata should be:

• Structured and machine-actionable — records expose defined fields rather than free text blobs, so they can be parsed and mapped automatically.
• Persistent-identifier friendly — the ecosystem links grants, funders, and research outputs via persistent identifiers such as Grant DOIs. Your records should carry PIDs for outputs and, where relevant, for grants, organizations, and people.
• Linkable across entity types — publications, data, software, projects, and organizations should be expressible as connected entities, not isolated listings.
• FAIR-aligned — findable, accessible, interoperable, and reusable, which is the standard OpenAIRE applies to research outputs generally.

A useful mental model: if a downstream system can take one record from your repository and reliably answer "what is this, who funded it, which organization produced it, and what else is it connected to?" — your metadata is on the right track.

A concrete example

Suppose a repository holds a dataset deposited by a research group. A minimally interoperable record would include a persistent identifier for the dataset, a title and description, the creator(s) with identifiers where available, the producing organization identified by a trusted identifier, the funding grant referenced by its Grant DOI, a license, and a stable landing-page URL. A non-interoperable version might have the same information buried in a PDF or in inconsistent free-text fields — technically public, but not aggregatable. The difference is not the amount of information but whether each element is separately addressable and machine-readable.

Who should use this service

The validation service is most relevant to:

If you are a researcher rather than a repository operator, this service is not the right entry point — you would instead be depositing into a repository that has already done this work.

How to approach compliance: steps and checkpoints

OpenAIRE does not publish a step-by-step wizard in the material available here, so the sequence below is the general method, with the validation service as the verification step.

1. Inventory what you expose. List the metadata formats and endpoints your repository or data source currently publishes (for example, an OAI-PMH endpoint or an API). Note which entity types you cover: publications, datasets, software, projects.
2. Map your fields to the expected elements. For each record type, check that identifiers, creators, organizations, funding references, license, and landing pages are present as separate, structured fields.
3. Add persistent identifiers where missing. Prioritize output PIDs and Grant DOIs, since OpenAIRE explicitly links grants, funders, and outputs through PIDs like Grant DOIs.
4. Run the interoperability validation. Use OpenAIRE's validation service for repositories and data sources to get a conformance assessment against OpenAIRE and EOSC standards.
5. Fix flagged issues and re-validate. Treat the first run as a baseline; iterate until the assessment is clean.
6. Confirm aggregation behavior. After validation, check that your records appear correctly linked — that outputs connect to the right projects, funders, and organizations — rather than merely appearing as standalone entries.

Expected result at each stage: after step 1 you know your coverage gaps; after step 3 your records carry the identifiers needed for linking; after step 5 you have a documented conformance result; after step 6 you can see your content participating in the interlinked graph rather than sitting in isolation.

Common sticking points

• Identifiers present but not persistent. A local record ID is not a PID. Linking to grants and organizations depends on resolvable identifiers.
• Funding metadata as free text. If grant information is a text string rather than a Grant DOI reference, it cannot be reliably linked to funders and projects.
• Organization names without identifiers. OpenAIRE offers disambiguation and mapping of research-performing organizations across data sources with trusted identifiers; unmatched organization strings are a frequent source of broken links.
• Treating validation as a one-off. Metadata drifts as systems change; re-running validation after major platform updates keeps conformance from silently degrading.

Where this fits in the wider OpenAIRE picture

Interoperability validation is one service among several that support the research lifecycle. It connects naturally to OpenAIRE's aggregation and interconnection of repository, CRIS, and journal content, and to the Scientific Knowledge Graph, which is where compliant metadata ultimately becomes usable for discovery and scientometrics. If your goal is a community-facing showcase rather than raw aggregation, the customizable, EOSC-ready gateways are the adjacent service; if your goal is a management plan, the Data and Software Management Plan tool is separate. Validation is the prerequisite step that makes the rest work.

For the authoritative requirements and to start a validation, use the interoperability validation service linked from OpenAIRE's services pages; the standards themselves are maintained in the EOSC context, so check both OpenAIRE's guidance and current EOSC interoperability documentation before finalizing your metadata profile.