Navigation
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. |