All Static Datasets
A listing of events or investigations assembled to aid users in locating data of interest. Each Entry in a Static Dataset has distinct begin and end times and a list of registered Data Subsets with optional DOIs to their persistent storage.
In This Page
5 static dataset entries , 17 data subsets
Datasets Used in an Academic Publication
Datasets placed in a static storage for a publication in an academic journal that required persistent access to the source data
2 Entries
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TNA Reports 8 Data Subsets
- Spectral analysis of local ground-based GNSS-derived TEC time series in view of its’ Sensitivity to Earthquakes in Aegean region
- High latitude lightning atmospherics belonging to transient luminous phenomena
- Ionospheric Irregularities Response to the April 2023 Major Geomagnetic Storm: A European Perspective
- Sensitivity of Ionospheric Disturbance detection by Swarm in time of strong Earthquakes in Aegean region
- Evaluation of a low-cost receiver for ionospheric monitoring
- Ionospheric influence on the propagation of ELF radio waves (PROPER)
- Characteristics of CIR-driven storm induced traveling ionospheric disturbances over mid-latitude Europe from ionosonde and LOFAR data (SUNDIAL)
- Radio scintillation studies for prospects of space weather forecasting and analyses
Training Datasets for a Machine Learning Model
Training dataset for a Machine Learning model allocated by the model designer and stored in a persistent repository for posterity. Catalog Entry registers the model, and Data Subset registers the training dataset. Retraining of the model results in registration of another Data Subset document for the same Catalog Entry.
1 Entry
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- TFT LSTID forecasting model for DB049: training period 01/01/2022-24/07/2024
- TFT LSTID forecasting model for JR055: training period 01/01/2022-30/06/2023
- TFT LSTID forecasting model for EB040: training period 01/01/2022-30/06/2023
- TFT LSTID forecasting model for SO148: training period 01/01/2022-27/04/2024
- TFT LSTID forecasting model for SO148: training period 01/01/2022-30/06/2023
- TFT LSTID forecasting model for DB049: training period 01/01/2022-30/06/2023
Data Pertaining to an Event
Subset of unpublished data (graphical, numerical) with distinct start and stop times that correspond to a registered event in the Event Catalogue
2 Entries
Data from an Experiment Campaign
Data collection during planned experiments and observation campaigns such as the World Day.