Linked Data (LD)#
The linked data module enables RDF (Resource Description Framework) integration with HDF5 files, bringing semantic web capabilities to your scientific data.
Background#
While HDF5 files provide a hierarchical structure for storing data and metadata, they lack standardized semantics. RDF provides a framework for describing resources with unique identifiers and relationships, enabling:
Global uniqueness: Persistent identifiers (e.g., ORCID, DOI) for researchers and data
Interoperability: Common vocabularies and ontologies for domain-specific terms
Machine-readable metadata: Enable automated discovery and integration
Knowledge graphs: Build interconnected datasets that can be queried with SPARQL
The h5rdmtoolbox ld module bridges HDF5 and RDF by enabling:
Structural RDF: Automatically converting HDF5 structure to RDF (groups, datasets, attributes)
Contextual RDF: Mapping HDF5 attributes to semantic concepts via ontologies
SHACL validation: Validating HDF5 data against RDF shapes
Serialization: Exporting to JSON-LD, Turtle, and other RDF formats
Key Concepts#
- Structural RDF
Automatically generated RDF from HDF5 structure (groups, datasets, datatypes).
- Contextual RDF
User-defined mappings from HDF5 attributes to semantic concepts.
- RDF Mappings
Define how HDF5 attributes map to RDF predicates and objects.
- SHACL Shapes
RDF shapes that HDF5 metadata must conform to.