intel / intel/predictive-maintenance-pipeline
Request to add attribution for Pipeline Defect Dataset (DOI: 10.34740/KAGGLE/DS/5294466)
- Dominant language
- Python
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- 3
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- 3
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Description
Hi team, I noticed that the datasets/pipeline_defects_detection folder schema and classes directly mirror the Pipeline Defect Dataset I created and host on Kaggle (DOI: 10.34740/kaggle/ds/5294466). I am incredibly excited to see this data structure supporting an Agentic Edge AI project! Could we add a quick line to the datasets/README.md or references citing the original Kaggle dataset to help other researchers trace the data origins?" i will be very happy if you cite me. as you know you are from intel .
@misc{mir_md_musleh_uddin_shaeek_2024,
title={Pipeline Defect Dataset},
url={https://www.kaggle.com/ds/5294466},
DOI={10.34740/KAGGLE/DS/5294466},
publisher={Kaggle},
author={Mir Md Musleh Uddin Shaeek},
year={2024}
}
Contributor guide
Research direction
Update datasets/README.md or the repository references section with attribution for the Pipeline Defect Dataset. Use the supplied Kaggle URL, DOI, author, title, publisher, and year; the work is done when the dataset origin and creator are clearly cited for researchers.
Written by the indexing model from the issue text.
Assessment
- Domain
- documentation
- Issue type
- Documentation
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Activity status
- Quiet
- Clarity
- Clearly specified
- Newbie friendliness
- 82/100