| --- |
| configs: |
| - config_name: default |
| data_files: |
| - split: test |
| path: sample.csv |
| size_categories: |
| - 100B<n<1T |
| tags: |
| - Seismology |
| language: |
| - en |
| pretty_name: CWA |
| --- |
| |
| # CWA Benchmark: A Seismic Dataset from Taiwan for Seismic Research |
|
|
| ## Dataset Description |
|
|
| This dataset includes a larger number of seismic events, especially high-magnitude. A comprehensive set of events collected by the |
| [Central Weather Bureau](https://scweb.cwa.gov.tw/en-US) in Taiwan. The CWA benchmark features over 40 attributes and ∼500,000 seismograms, providing |
| valuable data labels for various seismology-related tasks. In the future, we will keep updating the dataset to ensure its relevance and utility. |
|
|
| The entire dataset are released in [Seisbench](https://github.com/seisbench/seisbench), the dataset can be loaded properly by the following: |
|
|
| 1. Install Seisbench & HuggingfaceHub |
| ```shell |
| $ git clone https://github.com/seisbench/seisbench.git |
| |
| $ cd seisbench |
| $ pip install . |
| $ pip install --upgrade huggingface_hub |
| ``` |
|
|
| 2. Load the CWA dataset |
| ```python |
| import seisbench.data as sbd |
| |
| basepath = <path to metadata.csv and chunks.hdf5> |
| cwa = sbd.CWA(download_kwargs={'basepath': basepath}) |
| print(cwa.metadata.head()) |
| ``` |
|
|
| * Some parameters customizing the CWA dataset |
| - (Bool) ```merge```: Whether to load the merged version (CWASN + TSMIP + Noise), **default=True**. |
| - (String) ```subset```: Specify the seismographic network (CWASN, TSMIP, All), **default="All"**. |
| - (List) ```train_year```: The range of years used for the training set, **default=[2011, 2018]**. |
| - (List) ```dev_year```: The range of years used for the development set **default=[2019]**. |
| - (List) ```test_year```: The range of years used for the testing set, **default=[2020, 2021]**. |
| ```python |
| import seisbench.data as sbd |
| |
| merge = False |
| subset = "CWASN" |
| train_year = [2012, 2017] |
| dev_year = [2018, 2020] |
| test_year = [2021, 2021] |
| |
| basepath = <path to the directory of metadata.csv and chunks.hdf5> |
| cwa = sbd.CWA(subset=subset, |
| merge=merge, |
| download_kwargs={'basepath': basepath}, |
| train_year = train_year, |
| dev_year = dev_year, |
| test_year = test_year |
| ) |
| |
| print(cwa.metadata.head()) |
| ``` |
|
|
| --- |
| ## Overview of the CWA |
| | Attribute | CWASN | TSMIP | Noise | |
| |:---:|:---:|:---:|:---:| |
| | Events | 5,849 | 12,306 | x | |
| | Traces | 1,237,272 | 98,665 | 806,914 | |
| | p-picks | 1,237,272 | 98,665 | x | |
| | s-picks | 821275 | 98,665 | x | |
| | sampling rate | 100 | 200 | 100 | |
| | Multi-event | 196965 | 0 | x | |
| | Measurement | cm/s2, cm/s | cm/s2 | cm/s2, cm/s | |
| | Time period | 2012-2021 | 2011-2020 | 2012-2021 | |
|
|
| --- |
| ## Number of trace |
| * Categorized into 5 levels by five different pickers |
| * Noise samples are also provided |
| * Number of traces |
| | Level | Meaning | CWASN | TSMIP | |
| |:---:|:---:|:---:|:---:| |
| | 0 | The 3-component data are all zeros | 45,244 | 9,620 | |
| | 1 | None of the pickers predicted correctly | 174,720 | 3,046 | |
| | 2 | The seismic signal is interrupted | 714 | 0 | |
| | 3 | 1 or 2 pickers predicted correctly | 192,889 | 3,487 | |
| | 4 | More than 3 pickers predicted correctly | 823,705 | 82,512 | |
|
|
| # File size |
|
|
| | **2011** | **2012** | **2013** | **2014** | **2015** | **2016** | **2017** | **2018** | **2019** | **2020** | **2021** | **Noise** | **Total** | |
| |:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:|:----:| |
| | 1.7G | 40 G | 46 G | 41 G | 53 G | 57 G | 41 G | 83 G | 44 G | 43 G | 50 G | 176 G | 836 G | |
|
|
| --- |
| ## Station in CWA |
|  |
|
|
| --- |
| ## Event in CWA |
|
|
|  |
|
|
| --- |
| ## Acknowledgement |
| This work was supported by grants from the Central Weather Administration (CWA) of Taiwan and the National Science and |
| Technology Council of Taiwan (NSTC 112-2636-E-011-002, NSTC 112-2628-E-011-008-MY3, and NSTC 113-2640-B-002-005). |
| In addition, the authors acknowledge the support of the “Empower Vocational Education Research Center” at the National Taiwan |
| University of Science and Technology through the Featured Areas Research Center Program within the framework of the Higher |
| Education Sprout Project by the Ministry of Education (MOE) in Taiwan. The authors would also like to express our gratitude to the |
| National Center for High-performance Computing of the National Applied Research Laboratories (NARLabs) in Taiwan for providing |
| computational and storage resources. |
|
|
| --- |
| ## Citation |
| ```text |
| @misc{tang2024CWA, |
| title={The CWA Benchmark: A Seismic Dataset from Taiwan for Seismic Research}, |
| author={Kuan‐Wei Tang, Kuan‐Yu Chen, Da‐Yi Chen, Tai‐Lin Chin, and Ting‐Yu Hsu}, |
| howpublished={https://pubs.geoscienceworld.org/ssa/srl/article-abstract/doi/10.1785/0220230393/650394/The-CWA-Benchmark-A-Seismic-Dataset-from-Taiwan?redirectedFrom=fulltext}, |
| note={Early publication on Seismological Research Letters}, |
| year={2024}, |
| } |
| |
| ``` |
