This page provides some basic information, pointers and links to explanations of Ontologies for beginners in this field. (2JJI)
More focused discussions are planned for geo-spatial ontologies along with material to help develop such ontologies. As time permits these may be focused on specific efforts of the community including demonstrations, workshops and developmental efforts as part of the NSF Interop work. (2JCP)
Early Definition (2JCV)
An ontology holds information about what categories exist in the domain, what properties they have, and how they are related to one another. (Chandrasekaran et al. 1999) (2JCQ)
Ontology engineering is a relatively new discipline assembling a set of tasks for the development of ontologies. These may be a foundational set or for a particular domain. Ontology engineering, like data and software engineering involves a lifecycle starting with strategic views, going through the development activities of analysis and design to building the ontology using a representational language and testing of the final product - an ontology. (2JDF)
There are many reasons to build an ontology analyzing domain knowledge. An overall goal is that people often want to share a common understanding of the structure of information among people or software agents. In this case an ontology is used to make explicit the semantics and knowledge contained within efforts such as software applications as well as within enterprises and business modeling of particular domains. (2JDG)
As part of such an effort an ontology can be used to enable reuse of domain knowledge and to make domain assumptions explicit or to separate domain knowledge in a declarative form from the operational knowledge which can be implemented in software. (2JDH)
The expectation of ontological engineering is to help solve such things as data and system inter-operability problems that have at their base semantic (and pragmatic) issues. An example of this is challenge of bridging from human understanding of business and technical terms and how these are used in software applications. Ontology engineering For an introduction of this topic see: http://en.wikipedia.org/wiki/Ontology_engineering (2JDD)
While Ontological engineering has many steps the more recent publicized work has emphasized improved representations for ontological products using specially designed languages such as OWL (Web Ontology Language) developed as part of the Semantic Web effort. Ontologies are a core building block of the semantic technology stack of the Semantic Web effort. See http://en.wikipedia.org/wiki/Ontology_language and http://en.wikipedia.org/wiki/Semantic_Web (2JDE)
More recently a thrust into Linked Data -Linked Open Data has been emphasized by the Semantic Web effort and recent SOCoP demonstration work has taken this direction by converting small samples of some U.S. based open source geo data (USGS, Geonames, Census, Linked Geo Data [Open Street Map], DBPedia etc. into RDF (see below for a discussion of RDF) and hosting these as SPARQL endpoint(s.) (2JJJ)
Building Complex Domain Ontologies (2JCR)
A start on analysis for developing ontology may be to look at simple lexicons and/or controlled vocabularies. As Noy and Mcguinness point out ontologies defines a common vocabulary for researchers who need to share information in a domain. But the challenge is to take informal definitions and elevate them to machine-interpretable definitions of the basic domain concepts and relations among them. (2JCS)
One relation is that or Type and subtype. These can be structured by developing taxonomies where terms are related hierarchically and can be given distinguishing properties. Such efforts involve a chosen ontology engineering methodology over the ontology lifecycle. (2JCT)
More detail on methods from some approaches are at SOCoP/OntologyMethods (2JDN)
Simple Tools - RDF and RDFS (2JDJ)
One tool from Semantic Web work to start on the formalization of vocabularies is RDF (Resource Description Framework. RDF is an assertional language made up of three terms that was intended to be used to express propositions using precise formal vocabularies, particularly those specified using the REF Schema (RDFS) for access and use over the World Wide Web. in combination RDF and RDFS was intended to provide a basic foundation for more advanced assertional languages with a similar purpose. Essentially RDF triples denote relations between pairs of objects. Often the triple is thought of as a Subject-Verb Relation-Object. Thus RDF can informally express Circle isa Shape. While RDF was originally designed as a metadata data model for web information "resources" a semi-formal method has grown around the RDF formalism to capture simple conceptual description of information. Thus is added by the use of RDFS the simple RDF schema language RDFS (Resource Description Framework Schema). (2JJN)
RDFS offers a simple vocabulary to model class and property hierarchies and other basic schema primitives that can be referred to from RDF models. Thus RDFS provides a simple ontology that particular RDFy documents may be checked against to determine semantic consistency. (2JJO)
See http://www.w3.org/RDF/ and http://en.wikipedia.org/wiki/Resource_Description_Framework (2JDK)
Using WGS84 as a reference model RDF has been applied by a W3C Semantic Web Interest Group (SWIG)to build namespaces to represent lat(itude), long(itude) and other information about spatially-located things. (2JJP)
See http://www.w3.org/2003/01/geo/#status (2JDM)
Formal, complex domain ontologies' design provides an overall conceptual structure of the domain. This typically identifies the domain's principal concrete concepts and their properties and where concepts have named relationships with other concepts, like "aligned-with" or "near-to". (2JD7)
Often abstract concepts (e.g. Role, Situation) as organizing features, are employed to define new concepts. An ontology will often identify the relationships among the concepts and distinguish which concepts have instances properties. (2JD8)
One ontology often references or including supporting ontologies. These may be more specific and/or more general such as a top-level ontology (e.g. DOLCE http://en.wikipedia.org/wiki/Dolce). (2JD9)