ShExML: improving the usability of heterogeneous data mapping languages for first-time users.

Integration of heterogeneous data sources in a single representation is an active field with many different tools and techniques. In the case of text-based approaches-those that base the definition of the mappings and the integration on a DSL-there is a lack of usability studies. In this work we have conducted a usability experiment ( = 17) on three different languages: ShExML (our own language), YARRRML and SPARQL-Generate.

Intestinal microbiota alterations by dietary exposure to chemicals from food cooking and processing. Application of data science for risk prediction.

Diet is one of the main sources of exposure to toxic chemicals with carcinogenic potential, some of which are generated during food processing, depending on the type of food (primarily meat, fish, bread and potatoes), cooking methods and temperature. Although demonstrated in animal models at high doses, an unequivocal link between dietary exposure to these compounds with disease has not been proven in humans. A major difficulty in assessing the actual intake of these toxic compounds is the lack of standardised and harmonised protocols for collecting and analysing dietary information.