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README.md

@@ -20,4 +20,38 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+license: cc-by-4.0
+task_categories:
+- image-segmentation
+size_categories:
+- n<1K
 ---
+# Alpine Grassland Root Segmentation
+
+92 root images (2550x2196) with manual binary root/background masks from the 'Grassland' dataset, collected in alpine grasslands during a study on root growth and soil function. It is one of the nine root imaging datasets in a benchmark of 21 Transformer and ConvNet architectures for root segmentation. Images keep their image series (BidmerN, BidmerS, Phytotron2021) and the record's U-Net training/validation split. The dataset contains 92 images with pixel-level mask annotations.
+
+This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
+
+The original train/test/val split has been preserved in the `split` column.
+
+## Citation
+
+```bibtex
+@article{smith2026systematic,
+  title={A systematic comparison of transformers and ConvNets for root segmentation across nine datasets},
+  author={Smith, Abraham George and Lamprinidis, Sotiris and Seethepalli, Anand and York, Larry M. and Han, Eusun and Möhl, Patrick and Boulata, Kyriaki and Thorup-Kristensen, Kristian and Petersen, Jens},
+  journal={Plant Methods},
+  volume={22},
+  pages={52},
+  year={2026},
+  publisher={BioMed Central}
+}
+```
+
+
+The dataset itself can be cited as:
+
+Möhl, P., von Büren, R. S., &amp; Hiltbrunner, E. (2025). *Growth of alpine grassland will start and stop earlier under climate warming (dataset)* [Dataset]. figshare. https://doi.org/10.6084/M9.FIGSHARE.20440497.V2
+
+
+*This dataset was reformatted from its original format to match HuggingFace standards.*