| # Article-Release Dataset Downloads |
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| The finalized article-release dataset is hosted directly in this Hugging Face repository. |
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| ## Primary Download — Hugging Face |
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| | File | Format | View on Hugging Face | Direct download | |
| |---|---|---|---| |
| | `ALL_benchmark_W60.parquet` | Apache Parquet | [View file](https://huggingface.co/datasets/NifferLi/Cold-Chain-Transportation-Strawberry/blob/main/article_release/ALL_benchmark_W60.parquet) | [Download](https://huggingface.co/datasets/NifferLi/Cold-Chain-Transportation-Strawberry/resolve/main/article_release/ALL_benchmark_W60.parquet?download=true) | |
| | `ALL_benchmark_W60.xlsx` | Microsoft Excel | [View file](https://huggingface.co/datasets/NifferLi/Cold-Chain-Transportation-Strawberry/blob/main/article_release/ALL_benchmark_W60.xlsx) | [Download](https://huggingface.co/datasets/NifferLi/Cold-Chain-Transportation-Strawberry/resolve/main/article_release/ALL_benchmark_W60.xlsx?download=true) | |
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| The Parquet file is recommended for programmatic analysis. The Excel file is provided for convenient inspection and use in spreadsheet software. |
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| ## Backup Download — Google Drive |
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| If the Hugging Face preview or download is temporarily unavailable, the same article-release files can be downloaded from the following public Google Drive backup folder: |
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| [Open the Google Drive backup folder](https://drive.google.com/drive/folders/1nGwz-wM6gM68djXA60qpG-73-kPFidKW?usp=sharing) |
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| The backup folder contains: |
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| ```text |
| ALL_benchmark_W60.parquet |
| ALL_benchmark_W60.xlsx |
| ``` |
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| The Google Drive folder is configured as: |
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| > **Anyone with the link → Viewer** |
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| No access request should normally be required. |
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| ## Dataset Description |
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| Both files contain the same finalized article-release benchmark dataset in different formats. |
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| The dataset contains: |
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| - **14,398 rows** |
| - **107 columns** |
| - data from six strawberry cold-chain shipments; |
| - resampled multi-sensor temperature measurements; |
| - engineered W60 features; |
| - current risk-stage labels; |
| - future severe-risk prediction targets; |
| - explanation-consistency cause flags; |
| - data-quality, confidence, and audit-related fields. |
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| ## Recommended Format |
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| ### Parquet |
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| Use `ALL_benchmark_W60.parquet` for: |
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| - Python or R analysis; |
| - machine-learning experiments; |
| - preservation of data types; |
| - efficient loading and storage. |
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| ### Excel |
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| Use `ALL_benchmark_W60.xlsx` for: |
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| - manual inspection; |
| - spreadsheet-based review; |
| - convenient viewing of columns and values. |
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| ## Loading with Python |
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| ### Parquet |
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| ```python |
| from huggingface_hub import hf_hub_download |
| import pandas as pd |
| |
| repo_id = "NifferLi/Cold-Chain-Transportation-Strawberry" |
| |
| path = hf_hub_download( |
| repo_id=repo_id, |
| filename="article_release/ALL_benchmark_W60.parquet", |
| repo_type="dataset" |
| ) |
| |
| df = pd.read_parquet(path) |
| |
| print(df.shape) |
| print(df.head()) |
| ``` |
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| ### Excel |
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| ```python |
| from huggingface_hub import hf_hub_download |
| import pandas as pd |
| |
| repo_id = "NifferLi/Cold-Chain-Transportation-Strawberry" |
| |
| path = hf_hub_download( |
| repo_id=repo_id, |
| filename="article_release/ALL_benchmark_W60.xlsx", |
| repo_type="dataset" |
| ) |
| |
| df = pd.read_excel(path) |
| |
| print(df.shape) |
| print(df.head()) |
| ``` |
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| ## Loading Files Downloaded from Google Drive |
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| If the files were downloaded from the Google Drive backup folder, load them directly from the local directory: |
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| ```python |
| import pandas as pd |
| |
| df_parquet = pd.read_parquet("ALL_benchmark_W60.parquet") |
| df_excel = pd.read_excel("ALL_benchmark_W60.xlsx") |
| |
| print(df_parquet.shape) |
| print(df_excel.shape) |
| ``` |
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| ## Availability Note |
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| Hugging Face is the primary hosting and documentation platform for this dataset. |
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| The public Google Drive folder is maintained as a backup mirror to ensure continuous access if the Hugging Face file preview, content-delivery service, or direct download is temporarily unavailable. |
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| Both locations provide the same finalized article-release files. |
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| ## Citation |
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| When using this dataset, please cite the associated article: |
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| ```text |
| Li, H., Uygun, Ö., Yu, X., Zhou, Y., Chang, X., & Chen, C.-H. |
| A Human-Centric Edge-Oriented Decision Support System for Cold Chain Transportation: |
| Early Warning, Trigger-Time Explanation, and Prescriptive Action Ranking. |
| Advanced Engineering Informatics, forthcoming. |
| ``` |
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| The DOI and final bibliographic details will be added once available. |
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| The dataset repository may also be cited as: |
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| ```bibtex |
| @dataset{li_coldchain_transportation_strawberry_advei, |
| author = {Li, Hu}, |
| title = {Cold-Chain Transportation Strawberry Dataset for ADVEI Article Release}, |
| publisher = {Hugging Face}, |
| year = {2026}, |
| note = {Processed dataset for the accepted Advanced Engineering Informatics article} |
| } |
| ``` |
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| ## Contact |
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| For questions about the dataset, file contents, or download access, please open a discussion in the Hugging Face dataset repository. |