Skip to main content
zenodoopen

Training, Validation and Test Sets for paper 'A Little Data goes a Long Way: Automating Seismic Phase Arrival Picking at Nabro Volcano with Transfer Learning'

<p>Training, Validation and Test Data for model presented in&nbsp;paper &#39;A Little Data Goes A Long Way: Automating Seismic Phase Arrival Picking at Nabro Volcano with Transfer Learning&#39;, submitted to Journal of Geophysical Research: Solid Earth.</p> <p>Files:</p> <p>- train_events_2498.h5 = training set of seismic waveforms (events with P-/S-wave labelled arrivals only, i.e., no noise waveforms)</p> <p>- train_events_2498.pkl = event training set metadata (UTC P-/S-wave phase arrival times)</p> <p>- train_noise_2498.h5 = training set of seismic waveforms (noise sections only, i.e., no event waveforms)</p> <p>- train_noise_2498.pkl = noise training set metadata (UTC time&nbsp;for training noise waveforms)</p> <p>- val_events.h5 = validation set of seismic waveforms (events with P-/S-wave labelled arrivals only, i.e., no noise waveforms)</p> <p>- val_events.pkl = event validation set metadata (UTC P-/S-wave phase arrival times)</p> <p>- val_noise.h5 = validation&nbsp;set of seismic waveforms (noise sections only, i.e., no event waveforms)</p> <p>- val_noise.pkl = noise validation set metadata (UTC time&nbsp;for validation noise waveforms)</p> <p>- test.h5 = test&nbsp;set of seismic waveforms (events and noise)</p> <p>- test_events.pkl = event test set metadata (UTC P-/S-wave phase arrival times for test event waveforms)</p> <p>- test_noise.pkl = noise test set metadata (UTC time for test noise waveforms)</p> <p>- nabro_2011-247.mseed = 24 hours seismic data from Nabro Urgency Array (2011-09-04), saved in mseed format (e.g., can be read with obspy)</p> <p>- nabro_2011-269.mseed = 24 hours seismic data from Nabro Urgency Array (2011-09-26), saved in mseed format (e.g., can be read with obspy)</p> <p>&nbsp;</p> <p>Further details and code for reading and using&nbsp;these files can be found at the GitHub repo for this paper:&nbsp;<a href="https://github.com/sachalapins/U-GPD">https://github.com/sachalapins/U-GPD</a></p> <p>&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
0