Ontologies and Taxonomies
The mapping of information aiming to facilitate information
discovery is addressed by the introduction of ontologies and
taxonomies. These are descriptions of an information space
in a manner that is widely accepted by the stakeholders in
a thematic area. For example, ontologies exist for the description
of cultural information. Ontologies also exist for the description
of scientific information and data.
The word ontology comes from the Greek words “on”
and “logos”, the latter meaning reason. Ontologies
date back to the 17th century BC and the discipline of philosophy
in ancient Greece. The word taxonomy refers to the Greek word
“taxis”, which means order, division, and law.
- Conceptualization’ refers to an abstract model of
phenomena in the world by having identified the relevant
concepts of those phenomena.
- Explicit’ means that the type of concepts used,
and the constraints on their use are explicitly defined.
- Formal’ refers to the fact that the ontology should
be machine readable.
- 'Shared' reflects that ontology should capture consensual
knowledge accepted by the communities
An ontology is more than a taxonomy: Ontologies include richer
relationships between terms. It is these rich relationships
that enable the expression of domain-specific knowledge. This
is a key distinction.
In the modern world, Gruber worked with ontologies. According
to him, “an ontology is a formal, explicit specification
of a shared conceptualization”, where:
Ontologies and taxonomies are used for information modelling,
that is, they are modelling the real world, or somebody’s
perception of the real world.
Conceptual models can be created representing a wide range
of objects ranging from in-formation to processes. The goal
of conceptual is to narrow the gap between the real world
and the computer based representation of it. A good example
of varying perceptions of the real world is displayed in the
figure below, which shows how a cat is perceived by its owner
and by a veterinarian. Both presented perceptions are correct,
however they represent different viewpoints.
The above example leads to an important observation: information
must be modelled tak-ing into account the target group that
will consumer it as well as the ways through which it will