IGNITE and BIG4 researchers successfully created the new OpenBiodiv-LOD through information extraction and modelling of additional biodiversity entities. Furthermore, they made additional developments to OpenBiodiv-O ontology.
OpenBiodiv is a biodiversity knowledge graph that includes OpenBiodiv-LOD, a synthetic linked open dataset that integrates academic literature knowledge with the taxonomic backbone utilised by the Global Biodiversity Information Facility.
In this paper, researchers discuss how to utilise the LOD for biodiversity informatics use cases and give examples by providing solutions to several competency questions. They also investigate performance issues that arise due to the large amount of inferred statements in the graph and conclude that OWL-full inference is impractical for the project and that unnecessary inference should be avoided.
The authors envision OpenBiodiv-LOD as an integral part of the existing semantic network of biodiversity knowledge, based on HTTP identifiers and controlled vocabularies. By semantically enhancing and linking knowledge in OpenBiodiv to existing machine-readable data, biodiversity data quality and its potential for reuse are improved.
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