Update README.md

README.md

@@ -26,9 +26,12 @@ Repository for the tabular portion of the [Global Streetscapes dataset](https://
 
 ## Content Breakdown
 ```
-Global Streetscapes (62+ GB)
-├── data/ (37 GB)
-│   ├── 21 CSV files with 346 unique features in total and 10M rows each
+Global Streetscapes (74 GB)
+├── data/ (49 GB)
+│   ├── 21 CSV files with 346 unique features in total and 10M rows each (37 GB)
+│   ├── parquet/ (12 GB) (New)
+│       ├── 21 Parquet equivalents of the 21 CSV files (New)    
+│       ├── 1 combined Parquet file (New)
 ├── manual_labels/ (23 GB)
 │   ├── train/
 │   │   ├── 8 CSV files with manual labels for contextual attributes (training)
@@ -45,13 +48,38 @@ Global Streetscapes (62+ GB)
 ```
 
 ## Download Instructions
-Please follow this [guide](https://huggingface.co/docs/huggingface_hub/guides/download) from Hugging Face for download instructions. Please avoid using 'git clone' to download the repo as Git stores the files twice and will double the disk space usage to 124+ GB.
+Please follow this [guide](https://huggingface.co/docs/huggingface_hub/guides/download) from Hugging Face for download instructions. Please avoid using 'git clone' to download the repo as Git stores the files twice and will double the disk space usage.
 
 We have also provided a script `download_folder.py` to download a specifc folder from this dataset, instead of just a single file or the entire dataset.
 
 To download the imagery portion (10 million images, ~6TB), please follow the code and documentation in our [GitHub repo](https://github.com/ualsg/global-streetscapes).
 Our [Wiki](https://github.com/ualsg/global-streetscapes/wiki/2-Download-images) contains instructions and a demo on how to filter the dataset for a subset of data of your interest and download the image files for them.
 
+## Read More
+
+Read more about this project on [its website](https://ual.sg/project/global-streetscapes/), which includes an overview of this effort together with the background, [paper](https://doi.org/10.1016/j.isprsjprs.2024.06.023), examples, and FAQ.
+
+A free version (postprint / author-accepted manuscript) can be downloaded [here](https://ual.sg/publication/2024-global-streetscapes/).
+
+## Citation
+
+To cite this work, please refer to the [paper](https://doi.org/10.1016/j.isprsjprs.2024.06.023):
+
+Hou Y, Quintana M, Khomiakov M, Yap W, Ouyang J, Ito K, Wang Z, Zhao T, Biljecki F (2024): Global Streetscapes — A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics. ISPRS Journal of Photogrammetry and Remote Sensing 215: 216-238. doi:[10.1016/j.isprsjprs.2024.06.023](https://doi.org/10.1016/j.isprsjprs.2024.06.023)
+
+BibTeX:
+```
+@article{2024_global_streetscapes,
+ author = {Hou, Yujun and Quintana, Matias and Khomiakov, Maxim and Yap, Winston and Ouyang, Jiani and Ito, Koichi and Wang, Zeyu and Zhao, Tianhong and Biljecki, Filip},
+ doi = {10.1016/j.isprsjprs.2024.06.023},
+ journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
+ pages = {216-238},
+ title = {Global Streetscapes -- A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics},
+ volume = {215},
+ year = {2024}
+}
+```
+
 ## Contribution Guide
 We welcome contributions to this dataset! Please follow these steps:
 
@@ -71,29 +99,18 @@ For any questions, please contact us via [Discussions](https://huggingface.co/da
 
 ## Changelog
 
-**YYYY-MM-DD**
+**2025-02-19**
 
-## Read More
+**Added:**
 
-Read more about this project on [its website](https://ual.sg/project/global-streetscapes/), which includes an overview of this effort together with the background, [paper](https://doi.org/10.1016/j.isprsjprs.2024.06.023), examples, and FAQ.
+- New [data/parquet/](https://huggingface.co/datasets/NUS-UAL/global-streetscapes/tree/main/data/parquet) folder containing Parquet files for improved efficiency in large-scale data processing.
+  - 21 Parquet equivalents of the 21 CSV files
+  - 1 Parquet combining contextual.csv, metadata_common_attributes.csv, segmentation.csv, simplemaps.csv, ghsl.csv, perception.csv, places365.csv, and osm.csv
 
-A free version (postprint / author-accepted manuscript) can be downloaded [here](https://ual.sg/publication/2024-global-streetscapes/).
+**Change contributed by:**
 
-## Citation
+Donnelly, C., Hadjiivanov, A., & Kalverla, P. (2024). streetscapes. Zenodo. [https://doi.org/10.5281/zenodo.14283533](https://doi.org/10.5281/zenodo.14283533)
 
-To cite this work, please refer to the [paper](https://doi.org/10.1016/j.isprsjprs.2024.06.023):
+**Refs:**
 
-Hou Y, Quintana M, Khomiakov M, Yap W, Ouyang J, Ito K, Wang Z, Zhao T, Biljecki F (2024): Global Streetscapes — A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics. ISPRS Journal of Photogrammetry and Remote Sensing 215: 216-238. doi:[10.1016/j.isprsjprs.2024.06.023](https://doi.org/10.1016/j.isprsjprs.2024.06.023)
-
-BibTeX:
-```
-@article{2024_global_streetscapes,
- author = {Hou, Yujun and Quintana, Matias and Khomiakov, Maxim and Yap, Winston and Ouyang, Jiani and Ito, Koichi and Wang, Zeyu and Zhao, Tianhong and Biljecki, Filip},
- doi = {10.1016/j.isprsjprs.2024.06.023},
- journal = {ISPRS Journal of Photogrammetry and Remote Sensing},
- pages = {216-238},
- title = {Global Streetscapes -- A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics},
- volume = {215},
- year = {2024}
-}
-```
+[PR #6](https://huggingface.co/datasets/NUS-UAL/global-streetscapes/discussions/6) [Discussion #5](https://huggingface.co/datasets/NUS-UAL/global-streetscapes/discussions/5)