(Excerpt) (aswp) chap7 ontology Engineering

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• 1. main stages in the ontology Development Process
• (2). consider reuse.
• (3). enumerate terms.
• (4). Define taxonomy.
• (5). Define properties.
• (6). Define facets.
• (7). Define instances.
• (8). Check for anomalies.
• 7.3.1 codified bodies of expert knowledge
• 7.3.2 integrated vocabularies
• 7.3.3 upper-level Ontologies
• 7.3.4 topic hierarchies
• 7.3.5 linguistic resources
• 7.3.6 ontology Libraries

7 ontology engineering7.1 introduction7.2 constructing ontologies manually1. main stages in the ontology Development Process (1). Determine Scope

Developing an ontology is akin to defining a set of data and
Their structure for other programs to use.

In other words, an ontology is a model of a particle
Domain, built for a particle purpose.

Basic questions to be answered at this stage are:

What is the domain that the ontology will cover?

For what we are going to use the ontology?

For what types of questions shoshould the ontology provide
Answers?

Who will use and maintain the ontology?

(2). consider reuse.

There is almost always an ontology available from a third
Party that provides at least a useful starting point for our own ontology.

(3). enumerate terms.

Write down in an unstructured list all the relevant terms
That are expected to appear in the ontology.

(4). Define taxonomy.

These terms must be organized inTaxonomic hierarchy.

Opinions differ on whether it is more efficient/reliable
Do this in a top-down or a bottom-up fashion.

(5). Define properties.

This step is often interleaved with the previous one.

(6). Define facets.

Steps before this only require the expressivity provided
RDF Schema.

Facet:This refersPropertyFor exampleCardinality,
Required value, relational characteristic (For exampleWannry,
Transitivity, inverse property.)

What may happen at this stageInconsistencies:

Incompatible
Domain and range definitions for transitive, equalric, or inverse properties.

Cardinality
Properties are frequent sources of inconsistencies.

Requirements
On Property values can conflict with domain and range restrictions,

(7). Define instances.

Because of these large numbers, populating an Ontology
Instances is typically not done manually.

Often, instances are retrieved fromLegacy datasourcesSuch as databases.

Another often used technique isAutomatic Extraction of instances from a text corpus.

(8). Check for anomalies.

An important advantage of the use of owl over RDF Schema is
The possibility to detect inconsistencies in the ontology itself, or in the Set
Of instances that were defined to populate the ontology.

7.3 reusing existing Ontologies

Sources of existing ontologies:

7.3.1 codified bodies of expert knowledge

Codified:Coded

Medical domain, cultural domain, etc have some existing
Codified bodies.

7.3.2 integrated vocabularies

Sometimes attempts have been made to merge a number
Independently Developed vocabularies into a single large resource.
Semantics of such integrated resource is expected to be rather low
Nevertheless it will be a good starting point.

7.3.3 upper-level ontologies7.3.4 topic hierarchies7.3.5 linguistic resources

E.g. WordNet

7.3.6 ontology Libraries

Examples may be found at the ontology Engineering Group's
Web site and at the DAML web site.

The general question of importing ontologies and
Establishing mappings between different mappings is still wide open, and is
Considered to be one of the hardest (and most urgent) semantic web research
Issues.

7.4 using semiautomatic Methods

There are two core challenges for putting the vision of
Semantic Web into action:

First, one has to support the re-engineering task
Semantic enrichment for building the web of meta-data.

Second, one has to provide a means for maintaining and
Adopting the machine-Processible data that is the basic for the Semantic Web.

7.5 On-to-knowledge Semantic Web ubunturesuggested reading