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A Data-driven Approach for Core Biodiversity Ontology Development.- A deep learning-based approach for segmenting and counting reproductive organs from digitized herbarium specimen images using refined Mask Scoring R-CNN
- A Test Collection for Dataset Retrieval in Biodiversity Research
- BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data
- BiodivOnto: Towards a Core Ontology for Biodiversity
- Building high-quality merged ontologies from multiple sources with requirements customization
- Capturing and Semantically Describing Provenance to Tell the Story of R Scripts
- Comprehensive leaf size traits dataset for seven plant species from digitised herbarium specimen images covering more than two centuries
- Dataset search in biodiversity research: Do metadata in data repositories reflect scholarly information needs?
- Deep leaf: Mask R-CNN based leaf detection and segmentation from digitized herbarium specimen images
- ISTMINER: Interactive Spatiotemporal Co-occurrence Pattern Extraction: A Biodiversity case study
- Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles.
- PhenoDeep: A Deep Learning-Based Approach for Detecting Reproductive Organs from Digitized Herbarium Specimen Images
- ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
- Results of the Ontology Alignment Evaluation Initiative 2021
- Towards an Ontology Network for the reproducibility of scientific studies
- Towards Scientific Data Synthesis Using Deep Learning and Semantic Web
- Towards Tracking Provenance from Machine Learning Notebooks
- Understanding experiments and research practices for reproducibility: an exploratory study
- [Dai:Si] – A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data
Results of the Ontology Alignment Evaluation Initiative 2021
| Title: | Results of the Ontology Alignment Evaluation Initiative 2021 |
|---|---|
| Authors: | Mina Abd Nikooie Pour, Alsayed Algergawy, Florence Amardeilh, Reihaneh Amini, Omaima Fallatah, Daniel Faria, Irini Fundulaki, Ian Harrow, Sven Hertling, Pascal Hitzler, Martin Huschka, Liliana Ibanescu, Ernesto Jiménez-Ruiz, Naouel Karam, Amir Laadhar, Patrick Lambrix, Huanyu Li, Ying Li, Franck Michel, Engy Nasr, Heiko Paulheim, Catia Pesquita, Jan Portisch, Catherine Roussey, Tzanina Saveta, Pavel Shvaiko, Andrea Splendiani, Cássia Trojahn, Jana Vatascinová, Beyza Yaman, Ondrej Zamazal, Lu Zhou: |
| Source: | OM@ISWC 2021 |
| Date: | 2021-12-01 |
| Type: | Workshop Paper |
| Abstract: |
The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test |