Ontologies

ENVO is an ontology which represents knowledge about environments,environmental processes, ecosystems, habitats, and related entities

An ontology that describes phenotypic traits in plants. Each trait is a distinguishable feature, characteristic, quality or phenotypic feature of a developing or mature plant.

Variation Ontology, VariO, is an ontology for standardized, systematic description of effects, consequences and mechanisms of variations. VariO allows unambiguous description of variation effects as well as computerized analyses over databases utilizing the ontology for annotation. VariO is a position specific ontology that can be used to describe effects of variations on DNA, RNA and/or protein level, whatever is appropriate.

The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases, and for projects such as the GWAS catalog. It combines parts of several biological ontologies, such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology. EFO is developed by the EMBL-EBI Samples, Phenotypes and Ontologies Team (SPOT). We also add terms for external users when requested.

FALDO is the Feature Annotation Location Description Ontology. It is a simple ontology to describe sequence feature positions and regions as found in GFF3, DBBJ, EMBL, GenBank files, UniProt, and many other bioinformatics resources. The aim of this ontology is to describe the position of a sequence region or a feature. It does not aim to describe features or regions itself, but instead depends on resources such as the Sequence Ontology or the UniProt core ontolgy.

The Multi-scale Multi-step ontology (MS-O) is an ontology to describe transformation processes., Multi-scale Multi-step ontology (MS-O) est une ontologie permettant de d-crire des processus de transformation.

This standard extends IEEE 1872-2015 Standard for Ontologies for Robotics and Automation to represent additional domain-specific concepts, definitions, and axioms commonly used in Autonomous Robotics (AuR). This standard is general and can be used in many ways - for example, to specify the domain knowledge needed to unambiguously describe the design patterns of AuR systems, to represent AuR system architectures in a unified way, or as a guideline to build autonomous systems consisting of robots operating in various environments.

SAREF4LIFT is an ontology that extends SAREF for the Smart Lifts domain. This SAREF extension is based on a limited set of use cases and existing data models identified within available initiatives.

SAREF4BLDG is an extension of the SAREF ontology that was created based on the Industry Foundation Classes (IFC) standard for building information. It should be noted that not the whole standard has been transformed since it exceeds the scope of this extension, which is limited to devices and appliances within the building domain.

The objective of the paper is to show how the OAM can be used to realize seamless integration of product information, with an emphasis on assembly, throughout all phases of a product design

the main categories of cutting tool data and the relationships between them. It provides a general information model of data representation and information exchange for these categories, as well as an overview of the principles of product data exchange used in ISO 13399 as a whole, a description of the other parts of ISO 13399 and a method for transferring cutting tool data

The IOF-s mission is to create a suite of ontologies intended to support digital manufacturing by facilitating cross-system integration both within the factory and across an enterprise, in commerce between suppliers, manufacturers, customers and other trading partners, and throughout the various stages of the product life cycle. The IOF Core Ontology resides at the top of this suite from an architectural perspective and contains terms found in a number of operational areas of manufacturing. These common terms appear, or are anticipated to appear, in two or more of the ontologies of the suite. Additionally, as the architectural approach chosen by the IOF is to base all of its ontologies on a single foundational or top-level ontology - for which the IOF chose the Basic Formal Ontology or BFO - the Core Ontology contains a number of intermediate-level terms that derive from BFO and from which common industry terms are in turn derived. Such intermediate-level terms are most often domain independent - meaning they are found in other industries and domains, such as in the banking, insurance, and healthcare industries, or in the sciences, as in the physics, chemistry and biology domains. The IOF Core Ontology is developed and formalized as an ontology using both first-order logic and version 2 of the Web Ontology Language (OWL). The use of logic ensures that each term is defined in a way that is unambiguous to humans and can be processed by computers. All terms appearing in the ontology are reviewed and curated by a working group and consensus is reached by validating usage in the context of manufacturing domain use cases.