7 Ontology Engineering
7.1 Introduction
7.2 Constructing Ontologies Manually
1. 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 particular domain, built for a particular 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 should 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 in a taxonomic hierarchy.
Opinions differ on whether it is more efficient/reliable to 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 by RDF Schema.
facet: 这里是指property的各种约束，比如cardinality, required value, relational characteristic(如symmetry, transitivity,inverse property等。)
在这个阶段可能发生的inconsistencies:
incompatible domain and range definitions for transitive, symmetric, 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 with instances is typically not done manually.
Often, instances are retrieved from legacy datasources such as databases.
Another often used technique is the automated 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: 编成法典的
Medical domain, cultural domain, etc have some existing codified bodies.
7.3.2 Integrated Vocabularies
Sometimes attempts have been made to merge a number of independently developed vocabularies into a single large resource. The semantics of such integrated resource is expected to be rather low but nevertheless it will be a good starting point.
7.3.3 Upper-Level Ontologies
7.3.4 Topic Hierarchies
7.3.5 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 the Semantic Web into action:
First, one has to support the re-engineering task of 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.