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RASFF

Introduced by Alberto Nogales et al. in Food safety risk prediction with Deep Learning models using categorical embeddings on European Union data14 Sep 2020 archive 2025-07-28

In the actual globalized world, the transportation of goods between any country is something normal. Considering that the protocols in quality and security vary from one country to another, there is a risk with the products that do not comply with the legislation of a country cross the border. In the case of edible products, the importance of avoiding this kind of situation is even higher. Since 1979, European Union members were obligated to register any risk to public health-related with the food and feed that is traded alongside the territory. This information has been registered in a portal called Rapid Alert System for Food and Feed (RASFF). The content of this paper provides a deep description of a set of records that goes from September 1979 to September 2019 both included. Each record represents an issue registered by RASFF workers containing a set of generic features that all issues have in common, and a set of features that are considered details of the issue. The nature of the data in these features is only categorical except in one case, which is a string of characters that correspond to a subject. All the data was downloaded by using an automatic scrapper and using techniques to clean and transform it, so they can be stored as a .csv file. The potential use of the dataset is related to feature engineering, predictions, a search of behavior patterns, etc.

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Benchmarks archive 2025-07-28

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Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

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License archive 2025-07-28

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Modalities archive 2025-07-28

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Languages archive 2025-07-28

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Variants archive 2025-07-28

  • RASFF

1 variant name, as the archive lists them.

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