PIDfest 26

As data volumes and complexity grow the question of how to scale Persistent Identifier (PID) systems becomes increasingly important. In practice, data is often organized in hierarchies - from collections to datasets to individual files - raising a key challenge: Which level of detail truly benefits users whilst keeping the systems operational?

This session invites participants to share real-world use cases, challenges, and approaches to PID assignment across different domains. Depending on the context, PIDs at the collection or publication level may be sufficient for discovery and citation, while more granular identifiers are required for reproducibility, automated workflows, and machine actionability. However, increased granularity introduces overhead and complexity, potentially leading to unsustainable proliferation of identifiers.

We aim to bring together diverse perspectives from different stakeholders to explore how decisions about PID granularity are made in practice, and how to balance the trade-off between too many and too few PIDs.

Are you involved in or assisting researchers with either making datasets produced in HPC environments available for reuse or trying to find the data you need for your work and finding it utterly cumbersome? Have you ever wondered about how AI applications can best find the training data required for a specific task across infrastructural boundaries? Indeed, in many domains, data are created at large, distributed HPC centers but are not operationally assigned globally resolvable PIDs at the point of production, making it hard to identify, track, and reuse these datasets across infrastructures.

In this BoF, you will discuss how PIDs could be integrated directly into HPC workflows at simulation runtime, explore current technical ideas and challenges, and discuss what would be needed to make data practically immediately usable across federated HPC systems. The focus is on practical questions around data access, metadata, provenance, and interoperability.