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A Provenance-based Semantic Approach to Support Understandability, Reproducibility, and Reuse of Scientific Experiments- A Subjective Logic based Approach to Handling Inconsistencies in Ontology Merging
- Accessing and Integrating Citizen Science Sensor Data: Evaluation of OGC Sensor Observation Service Implementations
- ADOnIS: Managing Critical Zone Research Data Using Semantic Web Technologies
- Automatic Facet Generation and Selection over Knowledge Graphs
- Building Ontologies for Reuse – Lessons Learned from Unit Ontologies
- Efficient Bounded Jaro-Winkler Similarity Based Search
- Eleven years’ data of grassland management in Germany
- Entity Extraction in the Ecological Domain – A practical guide
- GMRs: Reconciliation of Generic Merge Requirements in Ontology Integration
- Measuring Morphological Functional Leaf Traits From Digitized Herbarium Specimens Using TraitEx Software
- On Using Subjective Logic to Build Consistent Merged Ontologies
- Partitioning of BioPortal Ontologies: An Empirical Study
- Semantic Relatedness as an Inter-Facet Metric for Facet Selection over Knowledge Graphs
- Species Association Knowledge Graph Construction – A Demo Paper
- Towards an ecological trait‐data standard
- Towards Knowledge Graph Construction using Semantic Data Mining
Species Association Knowledge Graph Construction – A Demo Paper
| Title: | Species Association Knowledge Graph Construction – A Demo Paper |
|---|---|
| Authors: | Dina Sharafeldeen, Alsayed Algergawy, and Birgitta König-Ries |
| Source: | 12th International conference on Semantic Web Applications and Tools in Healthcare and Life Sciences (SWAT4HCLS) |
| Place: | Edinburgh |
| Date: | 2019-12-10 |
| Type: | Demo |
| Abstract: |
Constructing knowledge graphs for new domains and linking them to existing ones has recently gained significant attention, especially in domains that have experienced a tremendous increase in available data such as biodiversity research. In this demo, we show a semantic data mining framework combining several knowledge bases to help in this task and show the feasibility of our framework using real-world datasets from a large-scale biodiversity project. |