3. – Lehrangebote – Lesson – Lecture –

Semantic Web Ontology



What is Ontology and why we need it?   –  What an ontology is for?  –  What is in an Ontology?

 "A revolution for information access and integration."

Klaus Kinkel   (German politicians, Foreign Minister a.D.)

Die globalisierte Datenwelt stellt Datenmengen zur Verfügung, die schlicht nicht mehr beherrschbar sind,
weder für den Einzelnen noch für Staaten.

The globalized world of data represents quantities of data that simply no more can be controlled,
either for individuals or for States

 "???? !!."


–  Short CONTENT  –


1.pointer ONTOLOGY for the WEB.

• Introduction  – What is in an Ontology? - Generally about Ontology - What an ontology is for?

•  Definitions –  ONTOLOGY.

•  Ontology’s essence –  (Definition).

•  Context – References – Weblinks:  –  (Introduction).

2.pointer The Semantic Web "layer cake" as presented by Tim Berners-Lee.
– A Layered Approach to Information Modeling and Interoperability on the Web.

3.pointer Ontology Languages.

•  SHOE:  Simple HTML Ontology Extensions. –  (early ontology language)

–  SHOE  Context – References – Weblinks:  –  (University of Maryland – HTML Ontology Extensions).

•  Development (schema) –  (History) of the web ontology languages.

•  OIL:  Ontology Interchange Language.

–  OIL  Context – References – Weblinks: –  (the Ontology Inference Layer).

•  DAML:  DARPA Agent Mark Up Language (or DAML- ONT).

–   DAML-S - Semantic Markup for Web Services.

–   DAML  Context – References – Weblinks:  –  (DARPA Agent Mark Up Language - DAML).

•  DAML+OIL:  Semantic Markup language for Web Resources.

–   DAML+OIL:  Context – References – Weblinks:  –  (Semantic Markup language for Web Resources).

•  OWL:  (W3C) - OWL: Web Ontology Language.

–  OWL  (W3C) - OWL: Web Ontology Language.

–  OWL-S  (W3C) - OWL-based Web Service Ontology.

–  References – Weblinks:  –  (W3C's – OWLWeb Ontology Language).

4.pointer Course – Lesson – Lecture.

•  Target group. – Entrepreneurs, professionnels and managers.

•  Aim of the course. – The lecture comprises the most important drafts of the semantic Web.

•  Content of the course. – About Web resources. –  (Axioms of Web architecture).

•  Internet and the WWW - Architecture of the WORLD WIDE WEB

–   Timeline of Computing History.   The University Museum, University of Pennsylvania

–   History of the Web.   Oxford Brookes University 2002.

–   Today - Architecture of the WORLD WIDE WEB

–   Tim Berners-Lee:   Design Issues.  Architectural and philosophical points.

–   Architecture of the World Wide Web, Volume One.   W3C Recommendation 15 December 2004.

–   The World Wide Web Consortium ( W3C ).  W3C Develops Web Standards and Guidelines.

• Course duration

5.pointer References ONTOLOGY - SEMANTIC WEB.
– Introductions and Overviews. / Applications and Initiatives.


top1. ONTOLOGY for the WEB.

The Semantic Web = a Web with a meaning.


Lattice of top-level categories

The term ONTOLOGY is borrowed from philosophy, where an Ontology is a systematic account of Existence.

In philosophy, an ontology is a theory about the nature of existence, of what types of things exist; ontology as a discipline studies such theories.

Ontology : The science or study of being; that department of metaphysics which relates to the being or essence of things,
or to being in the abstract.

For AI (Artificial-Intelligence) systems, what "exists" is that which can be represented.

Artificial-Intelligence (AI) and Web researchers have co-opted the term for their own jargon, and for them an

ontology is a document or file that formally defines the relations among terms.

The most typical kind of ontology for the Web has a Taxonomy and a set of Inference Rules.

Taxonomy : Classification, especially in relation to its general laws or principles; that department of science, or of a particular science or subject, which consists in or relates to classification; especially the systemic classification of living organisms.

The taxonomy defines classes of objects and relations among them.

Ontologies are often equated with taxonomic hierarchies of classes, class definitions, and the subsumption relation, but ontologies need not be limited to these forms. Ontologies are also not limited to conservative definitions, that is, definitions in the traditional logic sense that only introduce terminology and do not add any knowledge about the world (Enderton, 1972)

To specify a conceptualization one needs to state axioms that do constrain the possible interpretations for the defined terms.

Ontologies are a specification mechanism. An ontology is an explicit specification of a conceptualization.

Inference rules in ontologies supply further power.

Ontology in the computer science area, specifically in the AI community, it is considered an engineering artifact, constituted by a specific vocabulary used to describe a certain reality, plus a set of explicit assumptions regarding the intended meaning of the vocabulary words.
The assumptions has usually the form of a first order logical theory where vocabulary words appear as unary (concepts) or binary (relations) predicate names.
In its simplest form an ontology will describe a hierarchy of concepts, as it gets mores sophisticated suitable axioms are added.

Pragmatically, a common ontology defines the vocabulary with which queries and assertions are exchanged among software agents.
Ontological commitments are agreements to use the shared vocabulary in a coherent and consistent manner.

Many definitions of ontologies have surfaced in the last decade.
The term ontology has many meanings and shades of meaning.

It is possible to find in the literature several definitions of ontologies :

" An ONTOLOGY defines a common vocabulary for researchers who need to share information in a domain.
It includes machine-interpretable definitions of basic concepts in the domain and relations among them."

" An ONTOLOGY is a model of reality of the world and the concepts in the ontology must reflect this reality."

Ontology Development 101: A Guide to Creating Your First Ontology
Natalya F. Noy and Deborah L. McGuinness
Stanford University, Stanford, CA, 94305

" The subject of ONTOLOGY is the study of the categories of things that exist or may exist in some domain.
The product of such a study, called an ontology, is a catalog of the types of things that are assumed to exist in a
domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D.
The types in the ontology represent the predicates, word senses, or concept and relation types of the language L
when used to discuss topics in the domain D."

Building, Sharing, and Merging Ontologies.
John F. Sowa

" ONTOLOGY : A partial specification of a conceptual vocabulary to be used for formulating knowledge-level theories
about a domain of discourse.
The fundamental role of an ontology is to support knowledge sharing and reuse."

Glossary of Knowledge Modelling Terms.

"ONTOLOGY: A formal, explicit specification of how to represent the objects, concepts, and other entities in a particular system, as well as the relationships between them."

" Ontologies are specifications of the concepts in a given field and the relationships among those concepts."

" ONTOLOGY : explicit specification of a shared conceptualization that holds in a particular context"

A sum up from Guus Schreiber SWI, University of Amsterdam.

In the opinion of
•  Dieter Fensel and Frank van Harmelen, Vrije Universiteit , Amsterdam
•  Ian Horrocks, University of Oxford, Computing Laboratory, UK
•  Deborah L. McGuinness, Stanford University
•  Peter F. Patel-Schneider , Bell Laboratories
autors of:  OIL - An Ontology Infrastructure for the Semantic Web,
the best characterizes an ontology’s essence is this:

" An ONTOLOGY is a formal, explicit specification of a shared conceptualization."

In this context, conceptualization refers to an abstract model of some phenomenon in the world that identifies that phenomenon’s relevant concepts.

Explicit means that the type of concepts used and the constraints on their use are explicitly defined, (the precision of concepts and their relationships is clearly defined) and
a precise mathematical description hints the word formal, means that the ontology should be machine understandable.

Different degrees of formality are possible.

Shared reflects the notion that an ontology captures consensual knowledge - that is, it is not restricted to some individual but is accepted by a group.

Ontologies can be used to support a great variety of tasks in diverse research areas such as knowledge representation, natural language processing, information retrieval, databases, knowledge management, on line database integration, digital libraries, geographic information systems, visual information retrieval or multi agent systems.

Ontologies can enhance the functioning of the Web in many ways.

They can be used in a simple fashion to improve the accuracy of Web searches - the search program can look for only those pages that refer to a precise concept instead of all the ones using ambiguous keywords.

More advanced applications will use ontologies to relate the information on a page to the associated knowledge structures and inference rules.

" Knowledge Base: An informal term for a collection of information that includes an ONTOLOGY as one component.
Besides an ontology, a knowledge base may contain information specified in a declarative language such as logic
or expert-system rules, but it may also include unstructured or unformalized information expressed
in natural language or procedural code. "

By itself, logic says nothing about anything, but
the combination of logic with an ontology provides a language that can express relationships about the entities in the domain of interest.

" Knowledge Interchange Format - KIF - : a PARTICULAR LOGIC LANGUAGE, has been proposed as a standard to use to describe things within computer systems, e.g. expert systems, databases, intelligent agents, etc.
KIF is a prefix version of   First order predicate logic with Set Theory  (here - down)   with Logically comprehensive extensions to support non-monotonic reasoning, definitions and Model-theoretic semantics.

The language description includes both a specification for its syntax and one for its semantics."

" For the processing of the knowledge available in the Semantic Web are inference engine necessary. "
Inference engines deduce new knowledge from already specified knowledge.
Two different approaches are applicable here:
(1)logic based inference engines and (2) specialized algorithms (Problem Solving Methods).


–   What is an Ontology? – Autor: Tom Gruber –  <Thomas R. Gruber> – Knowledge Systems Laboratory, Stanford University.

–   Toward Principles for the Design of Ontologies - Used for Knowledge Sharing. (PDF) 1993  – <Thomas R. Gruber>  – KSL Stanford University.

–   Knowledge Interchange Format From Wikipedia, the free encyclopedia.

–   Knowledge Interchange Format (KIF). (PDF)

–   First-Order Predicate Calculus. (PDF)

–   First-Order Logic. (also known as first-order predicate calculus) - from Wolfram MathWorld.

–   First-Order Logic. From Wikipedia, the free encyclopedia.

–   Predicate logic. From Wikipedia, the free encyclopedia.

–   Glossary of First-Order Logic. Peter Suber, Department of Philosophy, Earlham College, Richmond, Indiana, 47374, U.S.A.

–   Set Theory. Stanford Encyclopedia of Philosophy.

–   Set Theory. What are sets? (PDF)

–   Set Theory. List of homepages of set theorists, inspired by Computability Theory

–   A history of set theory. The history of set theory...

–   4.4.5 Theory of Sets. Mathematical Markup Language (MathML) Version 3.0 - W3C Recommendation 21 October 2010.

–   Basic Notions of Modeltheoretic Semantics.

–   Model-Theoretic Semantics. OWL 1.1 Web Ontology Language - W3C Working Draft 8 January 2008.

–   Model-Theoretic Semantics. OWL 2 Web Ontology Language - W3C Working Draft 11 April 2008.

–   A Model-Theoretic Semantics. for DAML+OIL (March 2001).

Internet provides the infrastructure to enable global communication and ontologies provide a shared and common understanding of a domain,
their marriage allows the representation of domain knowledge,
that can be communicated between people and heterogeneous and distributed application systems.

trennlinie Semweb_LAYER

top 2. The Semantic Web "layer cake" as presented by Tim Berners-Lee.


top3. Ontology Languages.

 •   SHOE:   Simple HTML Ontology Extensions.(early ontology language)

–  SHOE  Context – References – Weblinks:

 •   Development (schema)  History of the web ontology languages.

 •   OIL:  Ontology Interchange Language.

–  OIL  Context – References – Weblinks:

 •   DAML:  DARPA Agent Mark Up Language (or DAML- ONT).

–  DAML  Context – References – Weblinks:

–  DAML-S - Semantic Markup for Web Services.

 •   DAML+OIL:  Semantic Markup language for Web Resources.

–  DAML+OIL  Context – References – Weblinks:

 •   OWL:  (W3C) - OWL: Web Ontology Language.

–   OWL - Web Ontology Language. (W3C)

–   W3C's OWL :  References – Weblinks:

–  OWL-S : OWL-based Web Service Ontology. (W3C)

While HTML allows us to visualize the information on the web, it doesn't provide much capability to describe the information
in ways that facilitate the use of software programs to find or interpret it.

Querying the Web today can be a frustrating activity because the results delivered by syntactically oriented search engines often do not match the intentions of the user.

This problem is caused by the Web’s lack of semantic structures that could be exploited during the search process.

However, XML has a limited capability to describe the relationships (schemas or ontologies) with respect to objects.

The use of ONTOLOGIES provides a very powerful way to describe objects and their relationships to other objects.

arrw08_26a SHOE: Simple HTML Ontology Extensions.


An important early ontology language was the Simple HTML Ontology Extensions (SHOE) language developed by students at the University of Maryland.

SHOE is a small extension to HTML which allows web page authors to annotate their web documents with machine-readable knowledge.

SHOE makes real intelligent agent software on the web possible.

HTML was never meant for computer consumption; its function is for displaying data for humans to read.

The "knowledge" on a web page is in a human-readable language , laid out with tables and graphics and frames in ways that we as humans comprehend visually.

Unfortunately, intelligent agents aren't human.

Even with state-of-the-art natural language technology, getting a computer to read and understand web documents is very difficult.

This makes it very difficult to create an intelligent agent that can wander the web on its own, reading and comprehending web pages as it goes.

SHOE eliminates this problem by making it possible for web pages to include knowledge that intelligent agents can actually read.

SHOE - Simple HTML Ontology Extensions, a KR language which allows web pages to be annotated with semantics.

SHOE allows authors to annotate their pages with ontology-based knowledge about page contents.

SHOE allows users to issue queries that are much more sophisticated than keyword search techniques, including queries that require retrieval of information from many sources.

SHOE: Context–References–Weblinks:

–   SHOE - Parallel Understanding Systems Group - Department of Computer Science - University of Maryland.

–   Semantic Interoperability on the Web (PPT)   - Autor:  Jeff Heflin and James Hendler, University of Maryland.

–   SHOE Publications - Parallel Understanding Systems Group - Department of Computer Science - University of Maryland.

–   SHOE: A Blueprint for the Semantic Web (PDF)   - Autor:  Heflin, J., Hendler, J., and Luke, S. Semantic Web. MIT Press, Cambridge, MA, 2003.

–   Shoes FAQ - A guide to....

–   The SHOE FAQ - Parallel Understanding Systems Group - Department of Computer Science - University of Maryland.

–   Simple HTML Ontology Extensions (SHOE) Cover Pages – OASIS, Organization for the Advancement of Structured Information Standards.

–   Simple Ontology Extensions (PPT)   Autor: Ahmet Selman Bozkir   - Hacettepe University Computer Eng. Dept.

–   Simple Ontology Extensions (PPT)   Autor: Ahmet Selman Bozkir   - Hacettepe University Computer Eng. Dept.

–   Towards the Semantic Web: Knowledge Representation in a Dynamic, Distributed Environment
Dissertation:   Jeffrey Douglas Heflin, Doctor of Philosophy,    Ph.D. Thesis,   University of Maryland, College Park. 2001. (PDF)


Development of the web ontology languages (History):
from RDF(S) to OWL Web Ontology Language.



arrw08_26a OIL: Ontology Interchange Language. (Ontology Inference Layer)

(OIL) (the Ontology Inference Layer)


OIL (Ontology Interchange Language / Ontology Inference Layer) proposes a
" a joint standard for integrating ontologies with exisiting and arising web standards ".

OIL is a Web-based representation and inference layer for ontologies, which combines the widely used modeling primitives from frame-based languages with the formal semantics and reasoning services provided by Description Logics(DL).

XML can be used as a serial syntax for OIL. The syntax of OIL is oriented towards XML and RDF.

Furthermore, OIL is the first ontology representation language that is properly grounded in W3C standards such as RDF/RDF-schema and XML/XML-schema.

OIL unifies three important aspects: Formal semantics and efficient reasoning support as provided by (1) Description Logics, (2) epistemological rich modeling primitives as provided by Frame languages, and a (3) standard proposal for syntactical exchange notations as provided by the Web community.

(1) Description Logics (DL) describe knowledge in terms of concepts and role restrictions that are used to automatically derive classification taxonomies. They provide theories and systems for expressing structured knowledge, for accessing it and reason-ing with it in a principled way.

Description Logics allow specifying a terminological hierarchy using a restricted set of first order formulas.

They usually have nice computational properties (often decidable and tractable, or at least seem to have nice average computational properties), but the inference services are restricted to classification and subsumption.

That means, given formulae describing a classes, the classifier associated with a certain description logic will place them inside a hierarchy, and given an instance description, the classifier will determine the most specific classes to which the particular instance belongs.
From a modeling point of view, Description Logics correspond to monadic/dyadic Predicate Logic statements with three variables.

(2) Frame-based systems provide as central modeling primitive classes (i.e., frames) with certain properties called attributes.
These attributes do not have a global scope but are only applicable to the classes they are defined for.
A frame provides a certain context for modeling one aspect of a domain.

(3) Web standards: XML and RDF. Given the current dominance and importance of the WWW, a syntax of an ontology language must be formulated using existing web standards for information representation. The XML schema syntax of OIL was mainly defined as an extension of XOL (XML-Based Ontology Exchange Language).
OIL is also defined on top of the Resource Description Framework RDF and RDF schema.

OIL shares many features with OKBC (Open Knowledge Base Connectivity) and defines a clear semantics and XML-oriented syntax for them.

In the same way that OIL provides an extension to OKBC (and is therefore downward compatible with OKBC) it also provides an extension to RDF and RDFS.

Based on its RDF syntax, ontologies written in OIL are valid RDF documents.

OIL extends the schema definition of RDFS.

Based on these extensions an ontology in OIL can be expressed in RDFS.


–   Ontology Interchange Language (OIL) Cover Pages – OASIS, Organization for the Advancement of Structured Information Standards.

–   OIL Home Page Ontoknowledge

–   OIL in a Nutshell - Autor: Dieter FenselIan HorrocksFrank van HarmelenStefan DeckerDr. Michael ErdmannMichel Klein

–   Questions and answers on OIL - Autor: Frank van HarmelenIan Horrocks

–   RESOURCES: Description Logics - maintained by Carsten Lutz - Univärsität Bremen.

–   DL-Learner: Learning Concepts in Description Logics  (PDF)   - <Jens Lehmann> - Department of Computer Science, University of Leipzig.

–   An Introduction to Description Logics (PDF)   - Autor: Daniele Nardi, Ronald J. Brachman.

–   Description Logics: Logics and Ontologies.  (PDF)   - <Enrico Franconi> - Department of Computer Science, University of Manchester.

–   The Role of Frame-Based Representation on the Semantic Web.
Autor:Ora Lassila - Nokia Research Center;
Deborah McGuinness - Knowledge Systems, AI Laboratory  Stanford University.

–  Schemabasierte P2P-Netzwerke - Techn. Hilfsmittel:RDF, OIL (PDF)   - Univärsität Leipzig.

arrw08_26a DAML: DARPA Agent Mark Up Language (or DAML- ONT)

•  DAML-S: Semantic Markup for Web Services.

US Defense Advanced Research Projects Agency.


RDF was developed by the W3C at about the same time as XML, and it turns out to be an excellent complement to XML, providing a language for modeling semi-structured metadata and enabling knowledge-management applications.

The RDF core model is successful because of its simplicity.

The W3C also developed a purposefully lightweight schema language, RDF Schema (RDFS), to provide basic structures such as classes and properties.

As the ambitions of RDF and XML have expanded to include things like the Semantic Web,

the limitations of this lightweight schema language have become evident.

Accordingly, a group set out to develop a more expressive schema language, DARPA Agent Markup Language (DAML).

"The goal of the DAML program is to create technologies that will enable software agents to dynamically identify and understand information sources, and to provide interoperability between agents in a semantic manner."

Although DAML is not a W3C initiative, several familiar faces from the W3C, including Tim Berners-Lee, participated in its development.

DAML designer Jim Hendler :
" has begun working with Berners-Lee and the World Wide Web Consortium to make sure that DAML fits with the W3C's plans for a semantic Web,
which would be based primarily on RDF (Resource Description Framework), the W3C's metadata technology for adding machine-readable data to the Web. "

Professor James A. Hendler ,   Department of Computer Science ,   Rensselaer Polytechnic Institute

The DAML language is being developed as an extension to XML and the Resource Description Framework (RDF).

"The DARPA Agent Mark-Up Language (DAML) (or DAML-ONT) is being designed as an XML-based semantic language that ties the information on a page to machine-readable semantics (ontology)."

RDF provide a basic feature set for information modeling.


RDF is very similar to a basic directed graph , which is a very well understood data structure in computer science.

This simplicity serves RDF very well, making it a sort of assembly language on top of which almost every other information-modeling method can be overlaid.

However, users have desired more from RDF and RDF Schema, including data types, a consistent expression for enumerations, and other facilities.

Logicians, some of whom see RDF as a possible tool for developing long-promised practical AI systems, have bemoaned the rather thin set of facilities provided by RDF.

In response the DARPA Agent Markup Language (DAML) sprang from a U.S. government-sponsored effort in August 2000, which released DAML-ONT, a simple language for expressing more sophisticated RDF class definitions than permitted by RDFS.

DAML: Context–References–Weblinks:

–  The DARPA Agent Markup Language Homepage.

–  About the DAML Language. – DAML Organisation.

–  DAML Briefings – DAML Organisation.

–  Knowledge Sharing Effort – DARPA – From Wikipedia, the free encyclopedia.

–  Directed Graphs (PDF)  – Graphs  – Princeton University

–  Directed Graphs – Russian Academic dictionaries and encyclopedias.

–  Directed Graphs – Autor: Kenneth R. Koehler –  University of Cincinnati, Raymond Walters College.

–  DARPA Agent Markup Language (DAML) Status and Tools. by Dan Connolly - W3C - World Wide Web Consortium.

–  DAML Tools – DAML Organisation.

–  Resource Description Framework (RDF) - W3C - World Wide Web Consortium.

up2_new_0_gif •  DAML-S: Semantic Markup for Web Services / DAML-Enabled Web Services.

The DARPA Agent Markup Language (DAML) program aims to allow one to mark up web pages to indicate the meaning of their content.

The Semantic Web should enable greater access not only to content but also to services on the Web.

Users and software agents should be able to discover, invoke, compose, and monitor Web resources offering particular services and having particular properties.

As part of the DARPA Agent Markup Language program, an ontology of services, called DAML-S, that will make these functionalities possible.

Among the most important web resources are those that provide services.

By service we mean Web sites that do not merely provide static information but
allow one to effect some action or change in the world, such as the sale of a product or the control of a physical device.

The Semantic Web should enable users to locate, select, employ, compose, and monitor Web-based services automatically.

To make use of a Web service, a software agent needs a computer-interpretable description of the service, and the means by which it is accessed. An important goal for DAML, then, is to establish a framework within which these descriptions are made and shared. Web sites should be able to employ a set of basic classes and properties for declaring and describing services, and the ontology structuring mechanisms of DAML provide the appropriate framework within which to do this.

Services can be primitive in the sense that they invoke only a single Web-accessible computer program, sensor, or device that does not rely upon anotherWeb service, and there is no ongoing interaction between the user and the service, beyond a simple response. For example, a service that returns a postal code or the longitude and latitude when given an address would be in this category. Or services can be complex, composed of multiple primitive services, often requiring an interaction or conversation between the user and the services, so that the user can make choices and provide information conditionally. One’s interaction with www.amazon.com to buy a book is like this; the user searches for books by various criteria, perhaps reads reviews, may or may not decide to buy, and gives credit card and mailing information.

DAML-S is meant to support both categories of services, but of course, complex services have provided the primary motivations for the features of the language.

The following four sample tasks will give the reader an idea of the kinds of tasks we expect DAML-S to enable.

1. AutomaticWeb service discovery.

2. Automatic Web service invocation.

3. Automatic Web service composition and interoperation.

4. AutomaticWeb service execution monitoring.

The service profile tells what the service does; that is, it gives the type of information needed by a service-seeking agent to determine whether the service meets its needs.

A service profile provides a high-level description of a service and its provider; it is used to request or advertise services with discovery/location registries.

Service profiles consist of three types of information:

•  a human readable description of the service;

•  a specification of the functionalities that are provided by the service; and

•  a host of functional attributes which provide additional information and requirements about the service that assist when reasoning about several services with similar capabilities.

A more detailed perspective on services is that a service can be viewed as a process.

The two chief components of a process model are the process, which describes a service in terms of its component actions or processes, and enables planning, composition and agent/service interoperation; and the process control model, which allows agents to monitor the execution of a service request.

DAML-S is an attempt to provide an ontology, within the framework of the DARPA Agent Markup Language, for describing Web services.

It will enable users and software agents to automatically discover, invoke, compose, and monitor Web resources offering services, under specified constraints.

arrw08_26a DAML+OIL: Semantic Markup language for Web Resources.

The DAML group soon pooled efforts with the Ontology Inference Layer (OIL), another effort providing more sophisticated classification, using constructs from frame-based AI.

Since then, an ad hoc group of researchers has formed the " Joint US/EU committee on Agent Markup Languages "

" The result of these efforts is DAML+OIL, a language for expressing
far more sophisticated classifications and properties of resources than RDFS."

The DAML+OIL ontology language is much richer in many ways than the SHOE language was.

DAML+OIL is a semantic markup language for Web resources.

The DARPA Agent Markup Language (DAML) is being developed as an extension to XML and the Resource Description Framework (RDF).

It builds on earlier W3C standards such as RDF and RDF Schema, and extends these languages with richer modelling primitives.

DAML+OIL provides modelling primitives commonly found in frame-based languages.

DAML+OIL (March 2001) extends DAML+OIL (December 2000) with values from XML Schema datatypes.

The language has a clean and well defined semantics.

A DAML+OIL knowledge base is a collection of RDF triples. ( What is an rdf triple?) (W3C rdf triple)

DAML+OIL prescribes a specific meaning for triples that use the DAML+OIL vocabulary.

The model-theoretic semantics specifies exactly which triples are assigned a specific meaning, and what this meaning is.

DAML+OIL shows how modern ontology languages are becoming more powerful and also more embedded on the web -- that is, they are more tied into advanced web languages.

( One key difference between DAML+OIL and SHOE is that DAML+OIL does not assume that the markup lives on the same page as the object being described.
In fact, the practice has become to have a separate page, using a ".daml" extension, which describes information in a manner intended for computers, not for humans.
The DAML+OIL ontology language is much richer in many ways than the SHOE language was.)

However, as the languages get more complicated, it gets harder for users to harness the full expressivity of the language, and harder for users to check to see whether the ontology someone else designed has the meaning they expect.

There are a number of research areas that are opened up by these languages, and their complexity, including issues of tool design, language display, and the use of the ontologies by more complex web agents.

DAML+OIL: Context–References–Weblinks:

–   DAML+OIL  – (DAML Organisation - December 2000)

–   An Axiomatic Semantics for RDF, RDF-S, and DAML+OIL  – Richard Fikes, Deborah L McGuinness, Knowledge Systems Laboratory, Stanford University.

–   An Axiomatic Semantics for RDF, RDF-S, and DAML+OIL  – Richard Fikes, Deborah L McGuinness – W3C Note 18 December 2001.

arrw08_26a OWL: Web Ontology Language.

•  OWL : Web Ontology Language.

•  OWL-S : OWL-based Web Service Ontology.


" The task of classifying all the words of language, or what's the same thing, all the ideas that seek expression, is the most stupendous of logical tasks.
Anybody but the most accomplished logician must break down in it utterly;
and even for the strongest man, it is the severest possible tax on the logical equipment and faculty."

Charles Sanders Peirce , letter to editor B. E. Smith of the Century Dictionary. –  (peirce.org)



" The art of ranking things in genera and species is of no small importance and very much assists our judgment as well as our memory. You know how much it matters in botany, not to mention animals and other substances, or again moral and notional entities as some call them. Order largely depends on it, and many good authors write in such a way that their whole account could be divided and subdivided according to a procedure related to genera and species.
This helps one not merely to retain things, but also to find them.
And those who have laid out all sorts of notions under certain headings or categories have done something very useful."

Gottfried Wilhelm Leibniz , New Essays on Human Understanding.

The World Wide Web and digital libraries are enormous repositories which concentrate huge volumes of distributed heterogeneous data.

The accessibility, maintenance, organization, preservation among other required tasks to manage these repositories as efficient as possible overcome human capabilities, in such a way that to carry them out, it is necessary the support of automatic processes or tools.

To achieve with this goal, an appropriated way to describe these repositories and their data machine understandable is required. Many alternatives have been developed, however, there is not a consensus to use one or a small set of them yet.

Artificial Intelligence is a research area which has proposed important approaches as data structures, relational data bases, mathematic logic, procedures, taxonomies among others. One of these proposals termed ontologies.

Ontologies emerged as an alternative to represent knowledge.

However, they have been used to support a great variety of tasks.

At present, there are applications of ontologies with commercial, industrial, academical or research focuses.

People, organizations and software programs must communicate, although different needs and backgrounds imply different viewpoints.

This divergence is natural and valuable, but it leads to problems in communication, interaction and understanding.

Ontologies are an alternative to address these kind of problems.

up2_new_0_gif •  OWL: Web Ontology Language.

OWL (Ontology Web Language) is being developed by the W3C Web-Ontology (WebOnt) Working Group (Closed).

Mail from Professor James Hendler: «  So Long and thanks for all the fish »

A new W3C OWL website has been developed for providing more information about OWL.

OWL has more facilities for expressing meaning and semantics than XML, RDF, and RDF-S, and thus OWL goes beyond these languages in its ability to represent machine interpretable content on the Web.

OWL is a revision of the DAML+OIL web ontology language incorporating lessons learned from the design and application of DAML+OIL.

OWL provides a basic infrastructure that allows a machine to make the same sorts of simple inferences that human beings do.


Re: Which kind of ontology is OWL specification? e-mail message: from Jim Hendler:

Received on Sunday, 4 January 2004 15:27:50 EST
- Previous message: Jim Hendler: "Re: "Transitive over" properties"
- In reply to: wwmm: "Which kind of ontology is OWL specification?"
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Sunday, 4 January 2004 15:27:51 EST
W3C home > Mailing lists > Public > public-webont-comments@w3.org > January 2004

From: Jim Hendler <References="hendler@cs.umd.edu>
Date: Sun, 4 Jan 2004

At 1:00 PM +0800 1/2/04, wwmm wrote:

> Is OWL specification a ontology?
> If so, Which kind of ontology is OWL specification?
> It is a representational ontology or task ontology?

> Yours sincerely

You ask a hard question - because it hinges on exactly what one defines as an ontology, a representational ontology, or a task ontology.
OWL is precisely specified in our documents and in a sense the only true answer to your question is "what is in the documents is what OWL is" --- that said, perhaps the following will be useful in helping you to answer your own question:

1 - OWL minimizes the "content" component purposely (by charter) - in other words OWL is not a specific set of content, but rather a convention for expressing content. There are some terms which are defined by OWL (or used consistently from RDF and RDF Schema), but in general it is meant to be a language for defining ontologies - not an "ontology" unto itself

2 - OWL has been used in many cases to define what has sometimes been called a "representational ontology" where that means soemthing like a specification of physical entities and their relationships. Many good examples of this can be found in the DAML Ontology Library [1]

3 - OWL has also been used to define "task" or "process" ontologies, where this term is used to mean a description of things in the world that change over time or a description of what the AI community has called in the past "planning operators." The best example I know of this can be found in the OWL-S work, which aims to use OWL to provide semantics for Web Service applications [2].

I hope this helps.
Jim Hendler

[1] http://www.daml.org/ontologies/
[2] http://www.daml.org/services/owl-s/1.0/

Professor James Hendler
Director, Semantic Web and Agent Technologies 301-405-2696
Maryland Information and Network Dynamics Lab. 301-405-6707 (Fax)
Univ of Maryland, College Park, MD 20742 240-277-3388 (Cell)

Professor Hendler has moved from the University of Maryland....
Professor James A. Hendler ,   Department of Computer Science ,   Rensselaer Polytechnic Institute

–  References, WebLinks:

– W3C's –  OWLWeb Ontology Language

OWL – W3C Recommendation –  2004-02-10
•   OWL – Use Cases and Requirements–   Publication history
•   OWL – Overview –   Publication history
•   OWL – Semantics and Abstract Syntax –   Publication history
•   OWL – Guide –   Publication history
•   OWL – Test Cases –   Publication history
•   OWL – Reference –   Publication history
OWL 2 – W3C Recommendation –  2009-10-27
•   OWL 2 –  Conformance –   Publication history
•   OWL 2 –  Direct Semantics –   Publication history
•   OWL 2 –  Mapping to RDF Graphs –   Publication history
•   OWL 2 –  New Features and Rationale –   Publication history
•   OWL 2 –  Document Overview –   Publication history
•   OWL 2 –  Primer –   Publication history
•   OWL 2 –  Profiles –   Publication history
•   OWL 2 –  Quick Reference Guide –   Publication history
•   OWL 2 –  RDF-Based Semantics –   Publication history
•   OWL 2 –  Structural Specification and Functional-Style Syntax –   Publication history
•   OWL 2 –  XML Serialization –   Publication history
•   rdf:PlainLiteral: –  A Datatype for RDF Plain Literals –   Publication history
OWL 2 – W3C Recommendation –  20010-06-22
•   RIF RDF and OWL Compatibility –   Publication history


up2_new_0_gif •  OWL-S : OWL-based Web Service Ontology.

OWL Web Ontology Language for Services (OWL-S )


–   OWL for Services (OWL-S) - Tools. DAML.org

–   XML declarative description with FIRST-ORDER LOGICAL CONSTRAINTs (FLCs) (PDF)
Computer Science Program, Shinawatra University, Pathumthani 12160, Thailand.
Computer Science and Information Management Program, Asian Institute of Technology, Pathumthani 12120, Thailand
Center for Information and Multimedia Studies, Hokkaido University , Sapporo 060, Japan.



Hyper Text Markup Language



Extensible Markup Language

Extensions for arbitrary domains and specific tasks.


Extensible Stylesheet Language

It provides a standard to describe mappings between different terminologies,
(a translation mechanism between XML documents).


Simple HTML Ontology Extensions

It is a XML compatible knowledge representation language for the web.
It allows page authors to annotate their web documents.
It is not actively maintained.


Resource Description Framework

Syntactic conventions and simple data models to represent semantics.
It supports interoperability aspects with object - attribute - value relationships.


Resource Description Framework Schema

Primitives to model basic ontologies with RDF.


Ontology Interchange Language

Primitives to model ontologies from frame - based languages,
formal semantics and reasoning support based on descriptive logic,
a proposal for syntatic interchange of annotations.
It is compatible with RDF Schema


DARPA Agent Markup Language

It is formed by DAML-ONT, (a language of ontologies) and
DAML - Logic (a language able to express axioms and rules),
it is less compatible with RDF than OIL.


Web Ontology Language

W3C Recommandation
2004-02-10; 2009-10-27; 20010-06-22;


Ontology Exchange Language

Simplicity, a generic approach to define ontologies.
It has two syntactical variants based on XML and RDF Schema.


4. Course – Lesson – Lecture.

topa. Target group.

Entrepreneurs, professionnels and managers.

topb. Aim of the course

The World Wide Web is presently a very large collection of mainly statistical documents, a large database without logic.

More and more businesses are completed over the Internet.

One of the most frequent problems is not only the availability of information, (then the Web-presence alone produced no marketing success yet), but rather also the intelligent settlement of the exchange of information, (B2B; B2C; Supply Chain Management, CRM,...etc.) electronic managements of strategic processes.

The present extension of the WWW is going mainly through meaningless associations.

Good businesses intelligence for Internet businesses or the generation of aim orientated offers for the E-COMMERCE, next to the simple needed information; extraction and interpretation of a problem are the technologies, which are available today.

Tim Berners-Lee, the inventor of the WWW, established the vision of a "Semantic Web", intelligent use of the WWW for the transmission and the exchange of contents that are intelligible also for machines and people.

It can be briefly described as an XML application to provide intelligent access to heterogeneous and distributed information.

Tim Berners Lee vision of Semantic Web project is a web where resources are also available to automated processes (agents) which could perform useful tasks such as an improved search (in terms of precision), resource discovery, information brokering and filtering
[Tim Berners-Lee 1999].

The notion of the semantic web as promoted by Tim Berners-Lee and by Jim Hendler as the focus of a major DARPA (Defense Advanced Research Projects Agency) -funded research effort, is to transform the current World Wide Web so that the information and services are understandable and useable by computers as well as humans. The Semantic Web will create an environment where software agents can readily perform sophisticated tasks and help humans find, understand, integrate, and use information.

The vision of the semantic web is to enable software agents to interact with each other without having to specify exchange formats or APIs a priori, like it is necessary in today's distributed systems.

In the semantic web, software agents operate as mediators between user needs and available information resources

The key distinguishing feature of the Semantic Web will be ONTOLOGIES which will enable software agents to find the meaning of the information on Web pages by following hyperlinks to definitions of key terms and rules for reasoning about them logically.

Ontologies will play a major role in supporting information exchange processes in various areas and networks.
A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies.

Ontologies play a crucial role for the semantic web.

The Semantic Web support automatic services, being based on the semantic descriptions.

Knowledge can be mediated only with the help of semantic.

The lecture comprises the most important drafts of the semantic Web, introduce the modelling - and analysis technologies as well and it gives an overview about the present developments

topc. Content of the course

Background knowledge about Web resources  –KEYWORDS– (concerning the meaning and the content):

top d. Internet & WWW - Architecture of the WORLD WIDE WEB


© Oxford Brookes University 2002
Birth of the World Wide Web  (WWW)


" KLICKEN Sie auf das BILD / Click on the Picture "
Birth of the Internet plaque at Stanford University

Today - Architecture of the WORLD WIDE WEB


Documents available from the Web or from any digital representation constitute a significant SOURCE of KNOWLEDGE
to be represented, handled and queried.

tope. Course duration

Ca. ... Std. Deeper involvement through private conversation is possible.
Reference: The advisor Dipl. Ing. Johann Magori -CAE system specialist- member of the engineer chamber in Hessen. I would like to clarify through this presentation the term or Semantic Web as a concept for numerous standards, technologies and ideas for the questions concerning the transmission, storage, processing of data, and clarify special outlooks of the Semantic Web.

- Private information is practically the source of every large modern fortune -

Oscar Wilde "

top 5. References « ONTOLOGY - SEMANTIC WEB. »

Short References  « ONTOLOGY - SEMANTIC WEB »  : Introductions and Overviews. / Applications and Initiatives

  • [1] The Semantic Web.(Tim Berners-Lee, James Hendler, Ora Lassila)

  • [1-A] Hypermedia and the Semantic Web: A Research Agenda.(Jacco van Ossenbruggen, Lynda Hardman, Lloyd Rutledge.)

  • [2] From Aristotle to the 'semantic web'.(Alan Gilchrist CURA Consortium , London, UK)

  • [3] Thesauri, taxonomies and ontologies - Some definitions.(Oxford English Dictionary - OED )

  • [4] Thesauri, taxonomies and ontologies - an etymological note.(Alan Gilchrist CURA Consortium , London, UK)

  • [5] The Semantic Web - on the respective Roles of XML and RDF.( Stefan Decker, Sergey Melnik, Ian Horrocks.......)

  • [6] A Layered Approach to Information Modeling and Interoperability on the Web. ( Sergey Melnik, Stefan Decker: Database Group-Stanford University)

  • [7] Adding formal semantics to the Web – building on top of RDF Schema. ( Jeen Broekstra, Michel Klein, Stefan Decker, Dieter Fensel, Ian Horrocks )

  • [8] Beyond RDF(S): The Ontology Perspective for the Semantic Web.( Prof. Dr. Rudi Studer, Institute AIFB, University of Karlsruhe)

  • [9] Ontology Learning for the Semantic Web.( Dr. Alexander Maedche, Prof. Dr. Steffen Staab, University of Karlsruhe, Ontoprise GmbH. Karlsruhe, Germany)

  • [10] OIL: An Ontology Infrastructure for the Semantic Web.(Dieter Fensel and Frank van Harmelen, Ian Horrocks, Deborah L. McGuinness.. )

  • [11] An Annotation Framework for the Semantic Web.(Prof. Dr. Steffen Staab, Dr. Alexander Maedche, Dr. Siegfried Handschuh)

  • [12] NOMOS: A Semantic Web Software Framework for Annotation of Multimodal Corpora.(John Niekrasz, Alexander Gruenstein)

  • [13] The Semantic Web: KR's Worst Nightmare?(Professor James Hendler presentation)

  • [14] Semantic Community Web Portals.(Steffen Staab,  Juergen Angele,  Stefan Decker,  Michael Erdmann,....)

  • [15] Semantic Interoperability on the Web.( Jeff Heflin,   James Hendler,   University of Maryland.)

  • [xx]     •   •   •    •  

  • [xx]     •   •   •    •  

  • [0] Timeline of Computing History.( Bob Carlson, Angela Burgess, and Christine Miller; IEEE Computer Society)

  • [01] History of the Web.(© Oxford Brookes University 2002)

  • [A] Generating answers! – in 21th Century. –


  • [C]COOPERATE PLUS.( LEONARDO DA VINCI" Community Vocational Training Action Programme "e-Learning")

  • [D] W3C - Short References -


The SEMANTIC WEB - Introductions and Overviews. / Applications and Initiatives.


arrw08_26a [A]

Generating answers! – in 21th Century. –



A federated STEP based - Systems Engineering -

Semantic Web based Services/Semantic Community Knowledge Web Portals EU/SME.


 Digital Library and Grid technology "e-Learning" :

" COOPERATE PLUS"  (MS-Word Format)

"LEONARDO DA VINCI" Community Vocational Training Action Programme -

in the field of IT & C and CAD/CAM for young professionals to develop teleworking projects.



[D]W3C - Short References :

  • W3C –  Extensible Markup Language (XML) 1.0 (Fifth Edition)
  • W3C –  XHTML™ 1.0 The Extensible HyperText Markup Language (Second Edition)
  • W3C –  XHTML™ 1.0 The Extensible HyperText Markup Language (Third Edition )
  • W3C –  XHTML™ 2.0
  • W3C –  HTML 5 –  A vocabulary and associated APIs for HTML and XHTML.
  • W3C –  Namespaces in XML 1.0 (Second Edition)
  • W3C –  W3C XML Schema Definition Language (XSD) 1.1 Part 1: Structures
  • W3C –  W3C XML Schema Definition Language (XSD) 1.1 Part 2: Datatypes.
  • W3C –  Cascading Style Sheets Level 2 Revision 1 (CSS 2.1) Specification
  • W3C –  Document Object Model (DOM) Level 2 HTML Specification. Version 1.0.
  • W3C –  Mathematical Markup Language (MathML) Version 3.0
  • W3C –  Scalable Vector Graphics (SVG) 1.1 Specification.
  • W3C –  Scalable Vector Graphics (SVG) Tiny 1.2 Specification.
  •     •   •   •   •  
  •     •   •   •   •  

The European Community has defined a new strategic goal:
- to become the most competitive and dynamic knowledge-based economy in the world. -

"European Council - March 2000-Lisbon / Barcelona 2002"

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