Digital agriculture increasingly relies on the generation of large quantities of images, from cellphones to drones and satellites. These images are processed with machine learning techniques to speed up the identification of objects, their classification, visualization, and interpretation. However, images must comply with the FAIR principles to facilitate their access, reuse, and interoperability. Ontologies, which are powerful tools for knowledge representation and reasoning, can effectively support image tagging for indexing, retrieval, and content comparison.

During this webinar we will learn about image annotation and the Bio-Image Semantic Query User Environment (BISQUE) project and understand how ontologies can enhance image tagging to make them FAIR compliant.

Speakers

Justin Preece

Senior Faculty Research Assistant at Oregon State University  

Justin Preece designs and develops software for genomics research, including web and desktop applications, data transformation software, and databases. He currently works on the BISQUE project and the Planteome project that aims to provide reference ontologies for describing the function, traits, and phenotypes of plant genes, varieties, and germplasms.

Pier Luigi Buttigieg

Data Scientist at the Alfred Wegener Institute

Pier Luigi Buttigieg’s work focuses on the application of bioinformatics and multivariate statistics to the diverse data sets derived from microbial ecology investigations. Concurrently, he develops and co-leads the Environment Ontology (ENVO) and the Sustainable Development Goals Interface Ontology (SDGIO) in support of semantically consistent data standardization across the sciences and global development agenda.