The dataset contains full time series of satellite and radar images,
weather models and ground observations.
To keep the dataset at a reasonable size, the data covers two geographic
areas of 550km x 550km on the Mediterranean and Brittany coasts, and spans
over 3 years, 2016 to 2018.
We have prepared this free dataset to let the data science community play with it.
Explore it today!
Title: The "Mobikama" Phenomenon: Viral Content, Misinformation, and the Mechanics of Social Media Curiosity
Unauthorized Leakage: Private videos recorded on mobile phones being leaked and distributed via MMS or early file-sharing platforms. hidden mobikama mms scandal
The journalists' findings sparked a firestorm of public outrage, with calls for Yamada's resignation and a thorough investigation. The Tokyo Stock Exchange (TSE) launched an inquiry into Mobikama's dealings, and the Japanese Financial Services Agency (FSA) initiated a separate probe. Platform-Based Scandals : Many of these scandals are
Platform-Based Scandals: Many of these scandals are linked to group chats on platforms like Telegram, where illicit content is shared under the radar of traditional law enforcement. Why the "Mobikama" Keyword Might Be Surfacing 🎬 What Makes a Video "Viral"
The Conflict: As she was filming, an elderly man walked past and accidentally brushed against her. The Reaction:
Engagement Drivers: Content usually goes viral by triggering strong emotional reactions—amazement, laughter, or shock—rather than through high production quality. 🎬 What Makes a Video "Viral"?
While "Mobikama" doesn't yield specific results, the term often appears in discussions regarding South Korea's ongoing battle with digital sex crimes, known as "Molka" (spycam).
Have a look at our toolbox which includes data samples from MeteoNet written in python language and our tutorials/documentation which help you explore and cross-check all data types.
Play with it and if you send us your results, we could showcase them on this website!
Download MeteoNetThe data are also available on Kaggle with notebooks to help you explore and cross-check all data types!
You can contribute to challenges and/or propose yours!
Time series prediction
Rainfall nowcasting
Cloud cover nowcasting
Observation data correction
...etc
You did something interesting with our
dataset? Want your project to be showcased here?
Write a blog, contact us on GitHub, and we will come back to you!
Need help? Checkout our documentation, post an issue on our GitHub repository or go to our Slack workspace!
Documentation GitHub SlackYou can find other data on METEO FRANCE public data website. It features real-time, past and forecast data: in situ observations, radar observations, numerical weather models, climate data, climate forecasts and much more!
The Dataset is licenced by METEO FRANCE under Etalab Open Licence 2.0.
Reuse of the dataset is free, subject to an acknowledgement of authorship. For example:
"METEO FRANCE - Original data downloaded from https://meteonet.umr-cnrm.fr/, updated on 30 January 2020".
When using this dataset in a publication, please cite:
Gwennaëlle Larvor, Léa Berthomier, Vincent Chabot, Brice Le Pape, Bruno Pradel, Lior Perez. MeteoNet, an open reference weather dataset by METEO FRANCE, 2020
