Plants from a handful of species provide the primary source of food for all people, yet this source is vulnerable to multiple stressors, such as disease, drought, and nutrient deficiency. With rapid population growth and climate uncertainty, the need to produce crops that can tolerate or resist plant stressors is more crucial than ever. Traditional plant breeding methods may not be sufficient to overcome this challenge, and methods such as highOthroughput sequencing and automated scoring of phenotypes can provide significant new (...) insights. Ontologies are essential tools for accessing and analysing the large quantities of data that come with these newer methods. As part of a larger project to develop ontologies that describe plant phenotypes and stresses, we are developing a plant disease extension of the Infectious Disease Ontology (IDOPlant). The IDOPlant is envisioned as a reference ontology designed to cover any plant infectious disease. In addition to novel terms for infectious diseases, IDOPlant includes terms imported from other ontologies that describe plants, pathogens, and vectors, the geographic location and ecology of diseases and hosts, and molecular functions and interactions of hosts and pathogens. To encompass this range of data, we are suggesting inOhouse ontology development complemented with reuse of terms from orthogonal ontologies developed as part of the Open Biomedical Ontologies (OBO) Foundry. The study of plant diseases provides an example of how an ontological framework can be used to model complex biological phenomena such as plant disease, and how plant infectious diseases differ from, and are similar to, infectious diseases in other organism. (shrink)

Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system is applied (...) to data generated by a wearable personal status monitoring (PSM) device. We demonstrate how annotated PSM data can be queried for contextualized vital signs as well as sensor algorithm configuration parameters. (shrink)