Sheeba Samuel

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 31

Top Topics

Semantic Enrichment

Machine Learning

Ontological Reasoning

Interstitial Lung

Top Venues

ESWC (Satellite Events)

Publications

Waqas Ahmed, Vamsi Krishna Kommineni, Birgitta König-Ries, Jitendra Gaikwad, Luiz M. R. Gadelha Jr., Sheeba Samuel
Evaluating the method reproducibility of deep learning models in the biodiversity domain. CoRR (2024)
Sheeba Samuel, Daniel Mietchen
FAIR Jupyter: a knowledge graph approach to semantic sharing and granular exploration of a computational notebook reproducibility dataset. CoRR (2024)
Vamsi Krishna Kommineni, Birgitta König-Ries, Sheeba Samuel
From human experts to machines: An LLM supported approach to ontology and knowledge graph construction. CoRR (2024)
Jihen Amara, Sheeba Samuel, Birgitta König-Ries
Integrating Domain Knowledge for Enhanced Concept Model Explainability in Plant Disease Classification. ESWC (1) (2024)
Dominik Kerzel, Birgitta König-Ries, Sheeba Samuel
MLProvLab: Provenance Management for Data Science Notebooks. BTW (2023)
Jihen Amara, Birgitta König-Ries, Sheeba Samuel
Concept explainability for plant diseases classification. CoRR (2023)
Samira Babalou, Sheeba Samuel, Birgitta König-Ries
Reproducible Domain-Specific Knowledge Graphs in the Life Sciences: a Systematic Literature Review. CoRR (2023)
Jihen Amara, Birgitta König-Ries, Sheeba Samuel
Concept Explainability for Plant Diseases Classification. VISIGRAPP (4: VISAPP) (2023)
Tarek Al Mustafa, Birgitta König-Ries, Sheeba Samuel
MLProvCodeGen: A Tool for Provenance Data Input and Capture of Customizable Machine Learning Scripts. BTW (2023)
Sheeba Samuel, Daniel Mietchen
Computational reproducibility of Jupyter notebooks from biomedical publications. CoRR (2023)
Sheeba Samuel, Birgitta König-Ries, Alsayed Algergawy
The role of ontology matching in ontology network development. OM@ISWC (2023)
Sheeba Samuel, Birgitta König-Ries
End-to-End provenance representation for the understandability and reproducibility of scientific experiments using a semantic approach. J. Biomed. Semant. 13 (1) (2022)
Luiz M. R. Gadelha Jr., Martin Hohmuth, Mahnoor Zulfiqar, David Schöne, Sheeba Samuel, Maria Sorokina, Christoph Steinbeck, Birgitta König-Ries
Toward a Framework for Integrative, FAIR, and Reproducible Management of Data on the Dynamic Balance of Microbial Communities. CoRR (2022)
Sheeba Samuel, Daniel Mietchen
Computational reproducibility of Jupyter notebooks from biomedical publications. CoRR (2022)
Luiz M. R. Gadelha Jr., Martin Hohmuth, Mahnoor Zulfiqar, David Schöne, Sheeba Samuel, Maria Sorokina, Christoph Steinbeck, Birgitta König-Ries
Toward a Framework for Integrative, FAIR, and Reproducible Management of Data on the Dynamic Balance of Microbial Communities. e-Science (2022)
Sheeba Samuel, Birgitta König-Ries
A collaborative semantic-based provenance management platform for reproducibility. PeerJ Comput. Sci. 8 (2022)
Dominik Kerzel, Sheeba Samuel, Birgitta König-Ries
Towards Tracking Provenance from Machine Learning Notebooks. KDIR (2021)
Sheeba Samuel, Alsayed Algergawy, Birgitta König-Ries
Towards an Ontology Network for the Reproducibility of Scientific Studies. JOWO (2021)
Nora Abdelmageed, Alsayed Algergawy, Sheeba Samuel, Birgitta König-Ries
BiodivOnto: Towards a Core Ontology for Biodiversity. ESWC (Satellite Events) (2021)
Sheeba Samuel, Birgitta König-Ries
ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks. IPAW (2021)
Maria Luiza Mondelli, Sheeba Samuel, Birgitta König-Ries, Luiz M. R. Gadelha Jr.
Capturing and Semantically Describing Provenance to Tell the Story of R Scripts. e-Science (2021)
Nora Abdelmageed, Alsayed Algergawy, Sheeba Samuel, Birgitta König-Ries
A Data-driven Approach for Core Biodiversity Ontology Development. JOWO (2021)
Sheeba Samuel, Frank Löffler, Birgitta König-Ries
Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles. IPAW (2021)
Sheeba Samuel, Frank Löffler, Birgitta König-Ries
Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles. CoRR (2020)
Sheeba Samuel, Birgitta König-Ries
ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks. CoRR (2020)
Sheeba Samuel, Kathrin Groeneveld, Frank Taubert, Daniel Walther, Tom Kache, Teresa Langenstück, Birgitta König-Ries, H. Martin Bücker, Christoph Biskup
The Story of an experiment: a provenance-based semantic approach towards research reproducibility. SWAT4LS (2018)
Sheeba Samuel, Birgitta König-Ries
Combining P-Plan and the REPRODUCE-ME Ontology to Achieve Semantic Enrichment of Scientific Experiments Using Interactive Notebooks. ESWC (Satellite Events) (2018)
Sheeba Samuel, Birgitta König-Ries
ProvBook: Provenance-based Semantic Enrichment of Interactive Notebooks for Reproducibility. ISWC (P&D/Industry/BlueSky) (2018)
Sheeba Samuel, Frank Taubert, Daniel Walther, Birgitta König-Ries, H. Martin Bücker
Towards Reproducibility of Microscopy Experiments. D Lib Mag. 23 (1/2) (2017)
Sheeba Samuel
Integrative Data Management for Reproducibility of Microscopy Experiments. ESWC (2) (2017)
Sheeba Samuel, Birgitta König-Ries
REPRODUCE-ME: Ontology-Based Data Access for Reproducibility of Microscopy Experiments. ESWC (Satellite Events) (2017)