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BiodivOnto: Towards a Core Ontology for Biodiversity.

, , , and . ESWC (Satellite Events), volume 12739 of Lecture Notes in Computer Science, page 3-8. Springer, (2021)

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Capturing and Semantically Describing Provenance to Tell the Story of R Scripts., , , and . e-Science, page 283-288. IEEE, (2021)A provenance-based semantic approach to support understandability, reproducibility, and reuse of scientific experiments.. University of Jena, Germany, (2019)Towards Tracking Provenance from Machine Learning Notebooks., , and . KDIR, page 274-281. SCITEPRESS, (2021)Evaluating the method reproducibility of deep learning models in the biodiversity domain., , , , , and . CoRR, (2024)MLProvLab: Provenance Management for Data Science Notebooks., , and . BTW, volume P-331 of LNI, page 965-980. Gesellschaft für Informatik e.V., (2023)REPRODUCE-ME: Ontology-Based Data Access for Reproducibility of Microscopy Experiments., and . ESWC (Satellite Events), volume 10577 of Lecture Notes in Computer Science, page 17-20. Springer, (2017)BiodivOnto: Towards a Core Ontology for Biodiversity., , , and . ESWC (Satellite Events), volume 12739 of Lecture Notes in Computer Science, page 3-8. Springer, (2021)Combining P-Plan and the REPRODUCE-ME Ontology to Achieve Semantic Enrichment of Scientific Experiments Using Interactive Notebooks., and . ESWC (Satellite Events), volume 11155 of Lecture Notes in Computer Science, page 126-130. Springer, (2018)A Data-driven Approach for Core Biodiversity Ontology Development., , , and . JOWO, volume 2969 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)ReproduceMeGit: A Visualization Tool for Analyzing Reproducibility of Jupyter Notebooks., and . IPAW, volume 12839 of Lecture Notes in Computer Science, page 201-206. Springer, (2021)