Approaches to measure class importance in Knowledge Graphs.

The amount, size, complexity, and importance of Knowledge Graphs (KGs) have increased during the last decade. Many different communities have chosen to publish their datasets using Linked Data principles, which favors the integration of this information with many other sources published using the same principles and technologies. Such a scenario requires to develop techniques of Linked Data Summarization.

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.

A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.

Background: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely related projects and initiatives, we need common ground, also known as a "commons.

SeDeLo: using semantics and description logics to support aided clinical diagnosis.

Automated medical diagnosis systems based on knowledge-oriented descriptions have gained momentum with the emergence of semantic descriptions. The objective of this paper is to propose a normalized design that solves some of the problems which have been detected by authors in previous tools. The authors bring together two different technologies to develop a new clinical decision support system: description logics aimed at developing inference systems to improve decision support for the prevention, treatment and management of illness and semantic technologies.