Active region magnetograms for solar flare prediction: Full resolution dataset

In this dataset, we provide a comprehensive collection of magnetograms from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO).  The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions as well as labels of corresponding flaring activity.  This dataset will be useful for image analysis or solar physics research related to magnetic structure, its evolution over time, and its relation to solar flares.  The dataset will be of interest to those researchers investigating automated solar flare prediction methods, including supervised and unsupervised machine learning (classical and deep), binary and multi-class classification, and regression.  This dataset is a minimally processed, user configurable dataset of consistently sized images of solar active regions that can serve as a benchmark dataset for solar flare prediction research.  This dataset consists of full resolution images (see usage notes below).

Methods
This dataset incorporates data from three main sources. First, in order to focus the image collection on ARs, we used the NOAA Space Weather Prediction Center (SWPC) Solar Region Summaries (SRS) (ftp://ftp.swpc.noaa.gov/pub/warehouse/) and parsed those text data to extract the date an AR appeared on disk and the number of days it was visible on disk.  Additionally, the SRS provide latitude and longitude of ARs which we use to postprocess the dataset.  Second, we download magnetogram images from SDO/HMI using the Joint Science Operations Center (JSOC) interface (http://jsoc.stanford.edu/ajax/lookdata.html) at a cadence of 720 seconds, centered at the NOAA AR centroid (tracked according to the Carrington rate), and with a spatial extent of 600x600 pixels.  Third, we used the SWPC Event Reports (ER) (ftp://ftp.swpc.noaa.gov/pub/warehouse/) to extract the AR number, peak flare time, and flare size in order to provide labels for those researchers investigating a supervised classification or regression problem.