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In computer sciences, an ontology stands for a set of concepts, associated terms and relationships defining a domain of knowledge. The aim of an ontology is to model this domain through a range of interconnected concepts. Main relationships used to link concepts are specialization relationships (hierarchical) and equivalence relationships (synonyms).

The @Web platform currently proposes four different ontologies:

• A Milk Microfiltration ontology (MICROFILTRATION) focusing on milk microfiltration processes to achieve optimization and enhance product quality
• A biorefinery ontology (IC2ACV) focusing on biomass-pretreatments relationships to achieve best glucose yields with minimum environmental impact
• A durum wheat ontology (Durum Wheat) focusing on durum wheat production, transformation and economical processes to improve sustainability and quality of wheat-based products
• An ontology on transfers of material (Transmat, MapOPT) focusing on package-food relationships to improve food conservation, sustainability and efficiency of packaging.

 Each ontology is structured around three categories of concepts:

• The symbolic concepts include studied objects and qualitative data
• The quantity concepts include quantitative data and associted units of measure
• The relation concepts describe relationships between studied objects, qualitative and quantitative data

 @Web also involves an annotation tool and a database in which are stored the annotations. Scientific papers are thus available by ontology as well as structured annotations, organized around the ontologies concepts.

More information and examples are given by ontology.