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Infrastructure and Population of the OpenBiodiv Biodiversity Knowledge Graph
Mariya Dimitrova1,2, Viktor E Senderov3, Teodor Georgiev2
1Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria Institute of Information and Communication Technologies, Bulgarian Academy of Sciences Sofia Bulgaria.
Biodiversity Data Journal
|October 25, 2021
Summary
OpenBiodiv-LOD, a biodiversity knowledge graph, has a new release integrating academic literature and taxonomic data. This update enhances biodiversity informatics by improving data modeling and avoiding impractical inference methods.
Area of Science:
- Biodiversity Informatics
- Knowledge Representation
- Linked Open Data
Background:
- OpenBiodiv is a biodiversity knowledge graph.
- It utilizes OpenBiodiv-LOD, a synthetic linked open dataset.
- This dataset combines academic literature with the Global Biodiversity Information Facility's taxonomic backbone.
Purpose of the Study:
- Introduce the new release of OpenBiodiv-LOD.
- Detail advancements in the OpenBiodiv-O ontology, data infrastructure, and R software packages.
- Demonstrate the utility of LOD in biodiversity informatics.
Main Methods:
- Information extraction from academic literature.
- Modeling biodiversity entities using the OpenBiodiv-O ontology.
- Transformation of literature into Resource Description Framework (RDF) format using R packages.
Main Results:
- A new release of OpenBiodiv-LOD is available.
- Developed OpenBiodiv-O, data storage, and R software packages for data transformation.
- Provided solutions to competency questions demonstrating LOD utilization.
Conclusions:
- OWL-full inference is impractical for large inferred statement graphs.
- Unnecessary inference should be avoided in the OpenBiodiv project.
- The enhanced OpenBiodiv-LOD facilitates biodiversity informatics applications.
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