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Solving the problem of ambiguous information.

Discover how OpenOrgs can help.

Identifying organisations involved in research can sometimes be a challenging task.

Organisations often use multiple names and identifiers in different places, which makes things confusing and hard to share information, find research, monitor activities, and develop of a linked open scholarly communication system.

To solve this problem, OpenAIRE created OpenOrgs. This tool mixes automated processes with human curation to clarify which organisations are involved in research. Its goal is to make information more accessible and help people find and recognize organisations easily.

So how does OpenOrgs work?

OpenOrgs works by using automated workflows and curator feedback
to deduplicate and manage organisational records.


Creation of Suggestions

First stage involves an automated workflow that is initiated to handle the deduplication of organisational records. The system identifies potential duplicate entries and works towards resolving these overlaps.

Once the deduplication process is complete, the system generates a set of suggestions which are essentially refined entries that need further review. 



In the second stage, data curators take over. They engage in manual editing of the organisation records which involves a detailed review and modification of the records as necessary.

The curation process is critical as it adds a layer of human oversight to ensure accuracy and relevance of the information in the records, refining the work done by the automated system.


Creation of Representative Organisations

This final stage involves another automated workflow. Based on the feedback and inputs provided by the data curators in the previous stage, this workflow creates a set of representative organisations.

The newly curated organisations are then integrated into the OpenAIRE Graph. This integration is significant as it makes the refined and verified organisational information publicly accessible and usable.