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README.md

@@ -1,43 +1,91 @@
 ---
-dataset_info:
-  features:
-  - name: material_id
-    dtype: string
-  - name: formula
-    dtype: string
-  - name: nsites
-    dtype: int64
-  - name: point_group
-    dtype: string
-  - name: space_group
-    dtype: int64
-  - name: volume
-    dtype: float64
-  - name: structure
-    dtype: string
-  - name: cif
-    dtype: string
-  - name: meta
-    dtype: string
-  - name: poscar
-    dtype: string
-  - name: eij_max
-    dtype: float64
-  - name: log(eij_max)
-    dtype: float64
-  - name: v_max
-    dtype: string
-  - name: piezoelectric_tensor
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 3587001
-    num_examples: 941
-  download_size: 1224873
-  dataset_size: 3587001
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: cc-by-4.0
+task_categories:
+  - tabular-regression
+  - tabular-classification
+tags:
+  - materials-science
+  - chemistry
+  - foundry-ml
+  - scientific-data
+size_categories:
+  - 1K<n<10K
 ---
+
+# A database to enable discovery and design of piezoelectric materials
+
+Dataset containing DFT-calculated piezoelectric properties for 941 materials
+
+## Dataset Information
+
+- **Source**: [Foundry-ML](https://github.com/MLMI2-CSSI/foundry)
+- **DOI**: [10.18126/p280-xrvg](https://doi.org/10.18126/p280-xrvg)
+- **Year**: 2022
+- **Authors**: de Jong, Maarten, Chen, Wei, Geerlings, Henry, Asta, Mark, Persson, Kristin A.
+- **Data Type**: tabular
+
+### Fields
+
+| Field | Role | Description | Units |
+|-------|------|-------------|-------|
+| material_id | input | Materials Project ID |  |
+| formula | input | Material composition |  |
+| nsites | input | Number of sites in the unit cell |  |
+| point_group | input | String denoting the point group of the structure |  |
+| space_group | input | Space group number |  |
+| volume | input | Volume of relaxed structure | Cubic Angstroms |
+| structure | input | Pymatgen structure representation of material |  |
+| eij_max | target | Maximum longitudinal piezoelectric modulus | C/m2 |
+| log(eij_max) | target | Log10 of eij_max | C/m2 |
+| v_max | target | Crystallographic direction, corresponding to maxim |  |
+| piezoelectric_tensor | target | Tensor, describing piezoelectric behavior (IEEE-fo | C/m2 |
+| cif | input | Material structure in CIF format |  |
+| meta | input | Summary of material metadata |  |
+| poscar | input | Material structure in POSCAR format |  |
+
+
+### Splits
+
+- **train**: train
+
+
+## Usage
+
+### With Foundry-ML (recommended for materials science workflows)
+
+```python
+from foundry import Foundry
+
+f = Foundry()
+dataset = f.get_dataset("10.18126/p280-xrvg")
+X, y = dataset.get_as_dict()['train']
+```
+
+### With HuggingFace Datasets
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("piezoelectric_tensor_v1.1")
+```
+
+## Citation
+
+```bibtex
+@misc{https://doi.org/10.18126/p280-xrvg
+doi = {10.18126/p280-xrvg}
+url = {https://doi.org/10.18126/p280-xrvg}
+author = {de Jong, Maarten and Chen, Wei and Geerlings, Henry and Asta, Mark and Persson, Kristin A.}
+title = {A database to enable discovery and design of piezoelectric materials}
+keywords = {machine learning, foundry}
+publisher = {Materials Data Facility}
+year = {root=2022}}
+```
+
+## License
+
+CC-BY 4.0
+
+---
+
+*This dataset was exported from [Foundry-ML](https://github.com/MLMI2-CSSI/foundry), a platform for materials science datasets.*