Vast amounts of data are available in the life science domains and its doubling every year. To fully exploit this wealth, data has to be distributed using FAIR (findable, accessible, inter-operable and reusable) guidelines. To support interoperability, an increasing number of widely used biological resources are becoming available in the Resource Description Framework (RDF) data model. RDF triples represent associations: a gene codes for a protein, which has a function associated to a reaction generating specific metabolites. The semantically linked triples, subject – predicate – object, can be joined together to form a knowledge network. Structural overviews of RDF resources are essential to efficiently query them assess their structural integrity and design, thereby strengthening their use and potential. Structural overviews can be derived from ontological descriptions of the resources. However, these descriptions often relate to the intended content instead of the actual content. We present RDF2Graph, a tool that automatically recovers the structure of an RDF resource. The generated overview allows to structurally validate newly created resources. Moreover, RDF2Graph facilitates the creation of complex queries thereby enabling access to knowledge stored across multiple RDF resources. RDF2Graph facilitates creation of high quality resources and resource descriptions, which in turn increases usability of the semantic web technologies.
- Java 1.8
- Blazegraph (will be provided)
- Galaxy (will be provided)
Jesse van Dam, Laboratory of Systems and Synthetic Biology, Wageningen University