%0 Generic %1 samuel2024fair %A Samuel, Sheeba %A Mietchen, Daniel %D 2024 %K jupyter knowledgegraph reproducibility software %T FAIR Jupyter: a knowledge graph approach to semantic sharing and granular exploration of a computational notebook reproducibility dataset

@misc{samuel2024fair, added-at = {2024-06-25T15:25:00.000+0200}, archiveprefix = {arXiv}, author = {Samuel, Sheeba and Mietchen, Daniel}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2a98c5bb7a2a58c6ac6121440113fde50/diglezakis}, eprint = {2404.12935}, interhash = {8039e9d6f542efe05b0a40eb448029c7}, intrahash = {a98c5bb7a2a58c6ac6121440113fde50}, keywords = {jupyter knowledgegraph reproducibility software}, primaryclass = {id='cs.CE' full_name='Computational Engineering, Finance, and Science' is_active=True alt_name=None in_archive='cs' is_general=False description='Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).'}, timestamp = {2024-06-25T15:25:00.000+0200}, title = {FAIR Jupyter: a knowledge graph approach to semantic sharing and granular exploration of a computational notebook reproducibility dataset}, year = 2024 }