5–6 Oct 2022
virtual, details will be shared with you after registration
Europe/Berlin timezone

New Approaches to Scalable FAIRification of Sample Data

1-26
Not scheduled
20m
virtual, details will be shared with you after registration

virtual, details will be shared with you after registration

Poster Postersession Postersession I

Speakers

Rory Macneil (Research Space)Mr Rorie Edmunds (DataCite)Dr Sara El-Gebali (SciLifeLab)

Description

Physical samples with informative metadata are more easily discoverable, shareable, and reusable. Metadata provides the framework for consistent, systematic, and standardized collection and documentation of sample information. This poster explores practical implementation of the FAIR Principles through creation of a framework centralized around biospecimens, linked datasets, sample information, and PIDs (Persistent Identifiers).

Two initiatives aimed at enhancing FAIRification of sample data will be described. The first, by SciLifeLab Data Centre, is to mobilize the community to identify a minimum set of attributes required for describing biospecimens with ontological mapping for semantic unambiguity and machine actionability. The goal is to facilitate interoperability and portability of sample information among multiple repositories and resources (e.g., e-Infrastructures). In addition, identifying the required attributes for registering biospecimen PIDs will enable coupling of descriptive metadata and objects in a FAIR and comprehensive manner.

The second initiative is development of the Inventory module of the RSpace electronic research notebook, which enables user-friendly and scalable sample collection and management and association of sample data and metadata with experimental data. The goal is similar to SciLifeLab’s: to facilitate portability and interoperability of sample information—in this case between RSpace and other tools, repositories, and e-Infrastructures.

Ultimately, both initiatives implement common elements to FAIRify sample data:

  • Association of variable domain-specific PIDs with sample data.
  • Incorporation of variable but standardized sample metadata formats that enable scalable submission to domain repositories.
  • User-friendly collection of sample data in the field.
  • Automated and scalable passage of sample data and metadata through systems and into external tools and resources.

Challenges faced and approaches to overcoming them will be outlined. The role of the IGSN–DataCite partnership, which is supporting global adoption, implementation, and use of IGSN identifiers by ensuring ongoing sustainability of IGSN PID infrastructure and by fostering a ‘Community of Communities of Practice’ across research domains, will be highlighted.

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PIDS, Controlled vocabularies, Samples, Metadata

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Primary authors

Rory Macneil (Research Space) Mr Rorie Edmunds (DataCite) Dr Sara El-Gebali (SciLifeLab)

Presentation materials