Data Sets

Food and feed health risk notifications in the European Union: a historical dataset of the issues registered in the Rapid Alert System for Food and Feed portal.

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). This dataset provides 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. Some features that can be highlighted are product, hazard, countries of origin, distribution, and destination, etc. The potential use of the dataset is related to feature engineering, predictions, a search of behavior patterns, etc.

Link: https://data.mendeley.com/datasets/yxkm4gs7zf/2

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Codes & Models

EEGRAPH

EEGraph is a Python library to model electroencephalograms (EEGs) as graphs, so the connectivity between different brain areas could be analyzed. It has applications in the study of neurologic diseases like Parkinson or epilepsy. The graph can be exported as a NetworkX graph-like object or it can also be graphically visualized.

 

LOV-scraper

Python script to download all vocabs and some information available from Linked Open Vocabulary (LOV) project (https://lov.linkeddata.es/dataset/lov/vocabs). The oupout is a csv file.

 

GEMA

GEMA is a Python library which can be used to develop and train Self-Organizing Maps (SOMs). It also allows users to classify new individuals, obtain reports and visualize the information with interactive graphs. mailing-list: gema-som@googlegroups.com. NOTE: GEMA has only been implemented in Python 3.0.

 

DBpedia-scrapper

A scrapper to create a corpus of documents from DBpedia based on its categories. Is it very useful for people interested in Deep Learning document classifiers.