FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset

Authors: Samuel, Sheeba, Mietchen, Daniel

Source: Transactions on Graph Data and Knowledge, Vol 2, Iss 2, Pp 4:1-4:24 (2024)

Subject Terms: knowledge graph, computational reproducibility, jupyter notebooks, fair data, pubmed central, github, python, sparql, Electronic computers. Computer science, QA75.5-76.95

File Description: electronic resource

Relation: https://drops.dagstuhl.de/storage/08tgdk/tgdk-vol002/tgdk-vol002-issue002/TGDK.2.2.4/TGDK.2.2.4.pdf; https://doaj.org/toc/2942-7517

Access URL: https://doaj.org/article/713f167755dc4db5b62813c6c8798cf4

Explainability of Deep Learning-Based Plant Disease Classifiers Through Automated Concept Identification

Authors: Amara, Jihen, König-Ries, Birgitta, Samuel, Sheeba

Subject Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence

Access URL: http://arxiv.org/abs/2412.07408

Harnessing multiple LLMs for Information Retrieval: A case study on Deep Learning methodologies in Biodiversity publications

Authors: Kommineni, Vamsi Krishna, König-Ries, Birgitta, Samuel, Sheeba

Subject Terms: Computer Science - Information Retrieval, Computer Science - Artificial Intelligence, H.3.3, I.2.7

Access URL: http://arxiv.org/abs/2411.09269

Enhancing Explainability in Multimodal Large Language Models Using Ontological Context

Authors: Amara, Jihen, König-Ries, Birgitta, Samuel, Sheeba

Subject Terms: Computer Science - Computer Vision and Pattern Recognition

Access URL: http://arxiv.org/abs/2409.18753

Evaluating the method reproducibility of deep learning models in the biodiversity domain

Authors: Ahmed, Waqas, Kommineni, Vamsi Krishna, König-Ries, Birgitta, Gaikwad, Jitendra, Gadelha, Luiz, Samuel, Sheeba

Subject Terms: Computer Science - Information Retrieval

Access URL: http://arxiv.org/abs/2407.07550

From human experts to machines: An LLM supported approach to ontology and knowledge graph construction

Authors: Kommineni, Vamsi Krishna, König-Ries, Birgitta, Samuel, Sheeba

Subject Terms: Computer Science - Computation and Language

Access URL: http://arxiv.org/abs/2403.08345

Toward a Framework for Integrative, FAIR, and Reproducible Management of Data on the Dynamic Balance of Microbial Communities

Authors: Gadelha, Luiz, Hohmuth, Martin, Zulfiqar, Mahnoor, Schone, David, Samuel, Sheeba, Sorokina, Maria, Steinbeck, Christoph, Konig-Ries, Birgitta

Source: 2022 IEEE 18th International Conference on e-Science (e-Science) ESCIENCE e-Science (e-Science), 2022 IEEE 18th International Conference on. :443-449 Oct, 2022

Relation: 2022 IEEE 18th International Conference on e-Science (e-Science)

Reproducible Domain-Specific Knowledge Graphs in the Life Sciences: a Systematic Literature Review

Authors: Babalou, Samira, Samuel, Sheeba, König-Ries, Birgitta

Subject Terms: Computer Science - Information Retrieval

Access URL: http://arxiv.org/abs/2309.08754

Concept explainability for plant diseases classification

Authors: Amara, Jihen, König-Ries, Birgitta, Samuel, Sheeba

Source: In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 246-253

Subject Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning

Access URL: http://arxiv.org/abs/2309.08739

Computational reproducibility of Jupyter notebooks from biomedical publications

Authors: Samuel, Sheeba, Mietchen, Daniel

Subject Terms: Computer Science - Digital Libraries, Computer Science - Computational Engineering, Finance, and Science

Access URL: http://arxiv.org/abs/2308.07333

Capturing and Semantically Describing Provenance to Tell the Story of R Scripts

Authors: Mondelli, Maria Luiza, Samuel, Sheeba, Konig-Ries, Birgitta, Gadelha, Luiz M. R.

Source: 2021 IEEE 17th International Conference on eScience (eScience) E-SCIENCE eScience (eScience), 2021 IEEE 17th International Conference on. :283-288 Sep, 2021

Relation: 2021 IEEE 17th International Conference on eScience (eScience)

Computational reproducibility of Jupyter notebooks from biomedical publications

Authors: Samuel, Sheeba, Mietchen, Daniel

Subject Terms: Computer Science - Computational Engineering, Finance, and Science

Access URL: http://arxiv.org/abs/2209.04308

Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles

Authors: Samuel, Sheeba, Löffler, Frank, König-Ries, Birgitta

Subject Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning

Access URL: http://arxiv.org/abs/2006.12117

ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks

Authors: Samuel, Sheeba, König-Ries, Birgitta

Subject Terms: Computer Science - Computers and Society

Access URL: http://arxiv.org/abs/2006.12110

BiodivOnto: Towards a Core Ontology for Biodiversity
Semantic web (Conference)

Authors: Abdelmageed, Nora, Algergawy, Alsayed, Samuel, Sheeba, König-Ries, Birgitta

Source: Lecture notes in computer science. 12739:3-8

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCCN606996777&indx=1&recIds=ETOCCN606996777

ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks
8th Workshop on Provenance and annotation

Authors: Samuel, Sheeba, König-Ries, Birgitta

Source: Lecture notes in computer science. 12839:201-206

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCCN606931989&indx=1&recIds=ETOCCN606931989

Machine Learning Pipelines: Provenance, Reproducibility and FAIR Data Principles
8th Workshop on Provenance and annotation

Authors: Samuel, Sheeba, Löffler, Frank, König-Ries, Birgitta

Source: Lecture notes in computer science. 12839:226-230

Availability: http://explore.bl.uk/primo_library/libweb/action/display.do?tabs=detailsTab&gathStatTab=true&ct=display&fn=search&doc=ETOCCN606932039&indx=1&recIds=ETOCCN606932039

Evaluating the method reproducibility of deep learning models in biodiversity research.

Authors: Ahmed, Waqas¹, ahmed.waqas@uni-jena.de, Kommineni, Vamsi Krishna^1,2,3, König-Ries, Birgitta^1,2,4, Gaikwad, Jitendra¹, Gadelha, Luiz¹, Samuel, Sheeba^1,4

Source: PeerJ Computer Science; Feb2025, p1-25, 25p

Hadoop Compatible Framework for Discovering Network Topology and Detecting Hardware Failures

Authors: Ventrapragada, Anusha, Samuel, Sheeba, Vidya, Varsha Raja, V, Prabha Satya Manepalli, Muralidharan, Shwetha, Rao, Shrisha

Source: 2012 Third International Conference on Services in Emerging Markets Services in Emerging Markets (ICSEM), 2012 Third International Conference on. :58-64 Dec, 2012

Relation: 2012 Third International Conference on Services in Emerging Markets (ICSEM)

Regulatory safety pharmacology and toxicity assessments of a standardized stem extract of Cassia occidentalis Linn. in rodents

Authors: Mugale, Madhav Nilakanth, Shukla, Shubha, Chourasia, Manish K., Hanif, Kashif, Nazir, Aamir, Singh, Sarika, Gayen, Jiaur R., Kumaravelu, Jagavelu, Tripathi, Raj Kamal, Mohrana, Baisakhi, Barthwal, Manoj k., Kumar, Akhilesh, Sharma, Deepak, Mohan, Divya, Srivastava, Anurag K., Samuel, Sheeba Saji, Kaleti, Navodayam, Bharti, Sachi, Srivastava, Anupama, Sharma, Divyansh, Meena, Anil Kumar, chandra, Ramesh, Yadav, Sudhaker, Bhushan, Bharati, Pandey, Sadan K., Agnihotri, Promod K., Bora, Himangsu K., Kanojiya, Sanjeev, Sharma, Sharad, Mishra, Prabhat Ranjan, Arya, Kamal R., Chattopadhyay, Naibedya, Rath, Srikanta Kumar, Bhadauria, Smrati

Source: In Regulatory Toxicology and Pharmacology July 2021 123