Pantelis TopalisVectorBase @ IMBB

Ontology is the science or study of being. In the field of biomedical informatics this is translated to an explicit formal specification of how to represent objects and other entities that are existing and the relationships those hold among them

An ontology may take a variety of forms, but necessarily it will include a vocabulary of terms, and some specification of their meaning. This includes definitions and an indication of how concepts are inter-related which collectively impose a structure on the domain and constrain the possible interpretations of terms.

Reference Ontologies are rich, axiomatic theories whose focus is to clarify the intended meanings of terms used in specific domains.

Application Ontologies provide a minimal terminological structure to fit the needs of a specific community.

Continuants (aka endurants)have continuous existence in time,preserve their identity through change,exist in toto whenever they exist at all.

Occurrents (aka processes)have temporal parts,unfold themselves in successive phases,exist only in their phases.

Independent entities: Organisms, Buildings, Environments are examples of independent entities.

Dependent entities require independent entities as their bearers. There is no run without a runner. Quality, Shape, Role, Propensity, Function, Status are all examples of dependent entities.

They are dependent on those independent continuants which are associated with them (agents, patients, media ...).

Class: what is general in reality, or in other words to what, is typically ‘concept’. Biological classes are for example cell or fat body development.

Instance: refers to what is particular in reality, to what are otherwise called ‘tokens’ or ‘individuals’ – entities (including processes) which exist in space and time.

The relations in biological ontologies connect classes as their relata.

We focus on genuinely ontological relations, which we take to mean relations that obtain between entities in reality, independently of our ways of gaining knowledge about such entities and independently of our ways of representing or processing such knowledge in computers.

We focus also on general-purpose relations - relations which can be employed, in principle, in all biological ontologies

Relations between classes (is_a).

Relations between instances (part_of).

Relations which relate a class with an instance (instance_of).

Directionality: Relations apply in a single direction. (leaf part_of plant)

Reflexivity: A relation is reflexive if it relates all entities with themselves. (For all p, p part_of p)

Symmetry: A relation is symmetrical if it applies in both directions. (is_next_to)

Transitivity: A relation is transitive if relationships of this type remain true across chains of links. (part_of, is_a)

part_of is_inverse_of has_part.

Leaf part_of plant Plant has_part leaves.

participates_in inverse_of has_participant

agent_in inverse_of has_agent.

Meaning is explicit. Meaning is human and computer readable. Ease of updating, no need to find terms in free

text and change them. Data transfer possible without loss of meaning. Reasoning to aid annotation. Reasoning to aid queries. Annotation of multiple bodies of data based on

underlying ontologies facilitates its integration to build another level of complexity.