This blog entry is mostly for myself. It serves as a note to remember the differences between common knowledge representations. Every information is taken from A Semantic Web Primer book which I highly recommend. The Semantic Web is a very huge topic and it is not easy to grasp the concepts by only searching for web resources. I needed one place, written by one author (group) who explains intelligibly all the different knowledge representation that play a major role in the Semantic Web in a consistent way. Here, I will list the knowledge representations together with their “you have to know” facts. In the end, you will have a brief overview on which representation carries semantics and what kind of logic constructs it supports.

XML and XSL

• XML allows the representation of information that is also machine-readable. Hence, XML can serve as a uniform exchange format between applications.
• XML separates content from formatting.
• XML is a meta-language for markup: it does not have a fixed set of tags but allows users to define tags of their own.
• Nesting of tags introduces structure. The structure of XML documents can be defined/enforced by DTDs or by XML Schemas. Note, the nesting of tags has no standard meaning.
• The semantics of XML documents is not accessible to machines, only to people.
• Collaboration and exchange are supported if there is an underlying shared understanding of the vocabulary. XML is well-suited for close collaboration, where domain- or community-based vocabularies are used. It is not so well-suited for global communication.
• Namespaces support the modularisation of DTDs and XML Schemas.
• Accessing and querying of XML documents can be done by using XPath.
• Transformation of XML documents can be done by using XSL and XSLT.

RDF and RDFS

• RDF provides a foundatioon for representing and processing metadara.
• RDF has a graph-based data model. Its key concepts are resource, property, and statement. A statement is a resource-property-value triple.
• RDF has an XML based syntax to support syntactic interoperability. XML and RDF complement each otherbecause RDF supports semantic interoperability. Note, XML is just one possible representation which is handy for interoperability.
• RDF has a decentralised philosophy and allows incremental building of knowledge, and its sharing and reuse.
• RDF is domain-independent.RDF Schema provides a mechanism for describing specific domains – for defining a terminology.
• RDF Schema is a primitive ontology language. It offers certain modelling primitives with fixed meaning. Key concepts of RDF Schema are class, subclass relations, property, subclass property relations, and domain and range restrictions.
• XML Schema constraints the structure of XML documents, whereas RDF Schema defines the vocabulary used in RDF data models.
• RDFS makes semantic information machine-accessible.
• RDF supports reification: making statements about statements. This introduces some complexity.
• In XML namespaces are only used for disambuigation purposes. In RDF external namespaces are expacted to be RDF documents defining resources, which are then used in the importing RDF document.
• RDF inference systems implement only a few dozen rules. All those rules can be efficiently implemented. These systems do not rely on first-order logic. The inference systems are sound and complete.
• Range definitions in RDF Schema are not used to restrict the range of a property, but rather to infer the membership of the range.
• There exist query languages for RDF and RDFS such as RQL or SPARQL. Those query languages dpo not need to understand the document structure. They operate on the graph data model.

OWL

• OWL is  teh proposed standard for Web ontologies. It allows us to describe the semantics of knowledge in a machine-accessible way.
• OWL build upon RDF and RDF Schema: (XML-based) RDF syntax is used; instances are defined using RDF descriptions; and most RDFS modelling primitives are used.
• Formal semantics and reasoning support is provided through the mapping of OWL on logics. Predicate logic and description logics have been used for this purpose.

Limitations of the Expressive Power of RDF Schema

•  Local scope of properties: We cannot declare range restrictions that applay to some classes only.
• Disjointness of classes.
• Boolean combinations of classes.
• Cardinality restrictions.
• Special characteristics of properties: transitive, inverse, functional, etc.

Formal Semantics and Reasoning Support

• Formal semantics describes the meaning of knowledge precisely.  It allows to reason about knowledge:
• Class membership.
• Equivalence of classes.
• Consistency.
• Classification.

A Formal semantics and reasoning support are usually provided by mapping an ontology language to a known logical formalism, and by using automated reasoners that already exist for those formalisms. OWL is (partially) mapped on a description logic, and makes use of existing reasoners such as FaCT and RACER. Description logics are a subset of predicate logic for which efficient reasoning support is possible.

 Species of OWL

• OWL Full: language
  • is powerfull,
  • but undecidable (incomplete; inefficient resoning support)
  • fully compatible with RDF
  • mapping to predicate logic needed
• OWL DL:
  • Application of OWL’s constructors to each other is disallowed
  • Looses full compatibility with RDF; but every legal OWL DL document is a legal RDF document
  • gains efficiency due to a mapping to description logic

• OWL Light:
  • no enumerated classes
  • no disjointness statements
  • no arbitrary cardinality

This page will be continuously updated.