Navigation
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
[Dai:Si] – A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data
| Title: | [Dai:Si] – A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data |
|---|---|
| Authors: | Fateme Shafiei, Felicitas Löffler, Sven Thiel, Kobkaew Opasjumruskit, Denis Grabiger, Pauline Rauh and Birgitta König-Ries |
| Source: | 3rd International Workshop on Semantics for Biodiversity (S4BioDiv), Proceedings of the Joint Ontology Workshops 2021 Episode VII: The Bolzano Summer of Knowledge co-located with the 12th International Conference on Formal Ontology in Information Systems (FOIS 2021), and the 12th International Conference on Biomedical Ontologies (ICBO 2021) |
| Place: | Bolzano, Italy |
| Date: | 2021-09-15 |
| Type: | Workshop Paper |
| URL: | http://ceur-ws.org/Vol-2969/paper4-s4biodiv.pdf |
| BibTex: |
@InProceedings{ShafieiEtAl2021,
author = {Shafiei, Fateme and L\"offler, Felicitas and Thiel, Sven and Opasjumruskit, Kobkaew and Grabiger, Denis and Rauh, Pauline and K\"onig-Ries, Birgitta},
booktitle = {S4BioDiv 2021: 3rd International Workshop on Semantics for Biodiversity, held at JOWO 2021: Episode VII The BolzanoSummer of Knowledge, September 11–18, 2021, Bolzano, Italy},
title = {[Dai:Si - A Modular Dataset Retrieval Framework with a Semantic Search for Biological Data},
year = {2021},
editor = {Sanfilippo, Emilio M. and Kutz, Oliver and Troquard, Nicolas and Hahmann, Torsten and Masolo, Claudio and Hoehndorf, Robert and Vita, Randi and Algergawy, Alsayed and Karam, Naouel and Klan, Friederike and Michel, Franck and Rosati, Ilaria},
url = {http://ceur-ws.org/Vol-2969/paper4-s4biodiv.pdf},
} |