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Table of Contents
FAIR data, dissemination and impact of your research
Use this section when you need to:
- understand FAIR data principles
- manage metadata effectively
- prepare research outputs for reuse
- disseminate content across platforms
- track impact and interoperability
Main roles:
- Contributors / Researchers
- Maintainers
- Advanced users
Related sections:
Dissemination begins after structured creation and publication work has already happened. A record that is well described, properly linked, moderated, and visible in the right context is easier to find, understand, cite, export, and reuse. This is why Metrics belongs here rather than in the earlier discovery chapter: analytics and impact are most meaningful once a record is already live and moving through the world.
Summary
FAIR data in HORTUS:
- improves discoverability
- enables reuse
- supports interoperability
- increases research impact
Key elements:
- metadata quality
- structured schemas
- dissemination strategy
- lifecycle management
The importance of FAIR data in research data management
Research data and research outputs become significantly more valuable when they can be found, understood, accessed, combined, and reused by other people (and by yourself in the future). This is the purpose of the FAIR principles a widely adopted framework for research data management that makes research outputs more useful and sustainable over time.
| FAIR principle | What it means in practice | How HORTUS helps |
|---|---|---|
| Findable | Others should be able to discover the output through search and structured description. | Marketplace records, keywords, metadata, project links, profile links, and search/filter controls improve findability. |
| Accessible | The output should be reachable through stable, understandable access routes. | Published pages, export routes, shareable links, and repository handoff increase access paths. |
| Interoperable | The description should be understandable across tools and systems. | Metadata management, structured fields, and integration routes support interoperable description. |
| Reusable | Others should be able to understand the object well enough to evaluate reuse. | Licences, metadata, references, project context, version-aware documents, and dissemination workflows strengthen reuse. |
FAIR is not a requirement to make everything open or public. A resource can be FAIR even when access is restricted, as long as the access conditions are clear and the metadata remains discoverable and meaningful.