add data and readme

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Australia-ASSA_01.zip

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README.md

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+---
+task_categories:
+- image-classification
+tags:
+- astrophysics
+- flares
+- solar flares
+- sun
+pretty_name: e-Callisto Solar Flare Detection
+size_categories:
+- 100K<n<1M
+---
+
+# e-Callisto Solar Flare Detection Dataset
+
+![](https://www.fhnw.ch/en/++theme++web16theme/assets/media/img/university-applied-sciences-arts-northwestern-switzerland-fhnw-logo.svg)
+[Institute of Data Science i4Ds, FHNW](https://i4ds.ch)
+
+## Overview
+This dataset comprises radio spectra from the [e-Callisto solar spectrometer network](https://www.e-callisto.org/index.html), annotated based on [labels from the e-Callisto database](http://soleil.i4ds.ch/solarradio/data/BurstLists/2010-yyyy_Monstein/). 
+The data was downloaded using the [ecallisto_ng Package](https://github.com/i4Ds/ecallisto_ng). It's designed for training machine learning models to automatically detect and classify solar flares.
+
+## Data Collection
+Data has been collected from various stations, with the following date ranges:
+
+| Station           | Date Range               |
+|-------------------|--------------------------|
+| Australia-ASSA_01 | 2021-02-13 to 2021-12-11 |
+| Australia-ASSA_02 | 2021-02-13 to 2021-12-09 |
+| Australia-ASSA_62 | 2021-12-10 to 2023-12-12 |
+| Australia-ASSA_63 | 2021-12-10 to 2023-12-12 |
+
+## Data Augmentation
+Due to the rarity of solar flares, we've augmented the dataset by padding the time series data around each flare event.
+
+## Caution
+The dataset underwent preprocessing and certain assumptions were made for label cleanup. Be aware of potential inaccuracies in the labels.
+
+## Split Recommendations
+The dataset doesn't include predefined train-validation-test splits. When creating splits, ensure augmented data does not overlap between training and validation/test sets to avoid data leakage.

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