In recent decades, exploring potential relationships between diseases has been an active
research field. With the rapid accumulation of disease-related biomedical data, a lot of …

Motivation Ontologies are widely used in biology for data annotation, integration and
analysis. In addition to formally structured axioms, ontologies contain meta-data in the form …

Many vocabularies and ontologies are produced to represent and annotate agronomic data.
However, those ontologies are spread out, in different formats, of different size, with different …

Linked Data (LD) aims to achieve interconnected data by representing entities using Unified
Resource Identifiers (URIs), and sharing information using Resource Description …

The Internet of Things (IoT) plays an ever-increasing role in enabling smart city applications.
An ontology-based semantic approach can help improve interoperability between a variety …

Motivation Infectious diseases caused by novel viruses have become a major public health
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …

The standardized identification of biomedical entities is a cornerstone of interoperability,
reuse, and data integration in the life sciences. Several registries have been developed to …

Background Ontologies and controlled terminologies have become increasingly important in
biomedical research. Researchers use ontologies to annotate their data with ontology terms …

The past decade has seen an explosion in the collection of genotype data in domains as
diverse as medicine, ecology, livestock and plant breeding. Along with this comes the …

In the last decade, ontologies have become widely adopted in a variety of fields ranging
from biomedicine, to finance, engineering, law, and cultural heritage. The ontology …