Persistent Identifiers (PIDs) are an important part of the scholarly ecosystem. However the current global approach to PIDs excludes many developing regions and contributes to creating significant inequalities in the scholarly ecosystem. The costs of minting DOIs from CorssRef and Datacite make them unaffordable in most parts of Africa, Asia, and Latin America, where there are often little or no budgets for these types of services. Furthermore, these international infrastructures do not support the needs of certain countries that have language requirements beyond English. Additionally, the consolidation of control within the hands of a few dominant entities in the global north also raises questions about inclusivity and true global representation in governance.
Because of this situation, several regional organisations have developed, or are developing, solutions for PIDs that are more appropriate for their local conditions (funding, language, etc.). These initiatives are very important as they provide persistence to the scholarly outputs in those countries/regions. However, since metadata from international, centralised PIDs services are being heavily relied upon by indexing and discovery systems that track and analyse research impacts, there is a risk that these resources will be ignored and therefore not recognised on an equal setting as those resources whose metadata is included in DataCite or CrossRef.
In November 2024, COAR launched a Task Force on Sustainable PIDs Models to develop a path forward and strategies for distributed PIDs initiatives that (1) supports the needs of a variety of regions, and (2) ensures international interoperability and discoverability of resources across different initiatives.
Objectives
- Recommend a common approach to distinguish resource types in the metadata aggregations for PIDs
- Share information about current initiatives
- Identify requirements for discoverability
- Define metadata and other interoperability requirements
- Propose a conceptual model whereby these initiatives are included in the global scholarly corpus
- Developing solutions that support different language and alphabets / characters
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