Juan Chamero

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Darwin versus W3C Visions - V

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Web Semantic

Darwin Vision versus W3C Vision- IV

TBL and OSI Seven L:ayers Models

W3C versus Darwin, two polar approaches that could reinforce each other

Dr. Juan Chamero, Esta dirección electrónica esta protegida contra spambots. Es necesario activar Javascript para visualizarla , Buenos Aires, Argentina February 15th 2009






I- Tim Berners Lee Seven Layers Model

seven layers model 


May 17th 2001 Tim Berners Leee Seven Layers Model: The Semantic Web, Scientific American



Introduction to the Semantic Web Vision and Technologies, Part 2, Foundations, from Cody Burleson;, as Oct 4th 2007

A Semantic Web Status Model, by Aurona Gerber, Meraka Institute, from South Africa,



Layer 1

Layer 1 comprises Unicode and URI (Uniform Resource Identifier) technologies. The function of these technologies is to provide a unique identification mechanism for upper language technologies.

Unicode: Unicode aims to uniquely identify the characters in all the written languages by assigning a unique number to each character. The Unicode Standard (Universal Character Set, Unicode/ISO10646) specified by the Unicode Consortium is the universal character encoding standard used for representation of text for computer processing. This standard supports three encoding mechanisms, UTF-8, UTF-16 and UTF-32, allowing the same data to be encoded in a byte, word or double word format. The emergence of the Unicode standard and the availability of supporting tools are amongst the most significant recent global software technology trends. Unicode replaces the use of legacy character sets and it allows data and text to be exchanged internationally between different systems.

URI: A URI (Uniform Resource Identifier), defined as a compact string of characters that can be extended, is used to identify an abstract or physical resource. A resource is defined as an entity that has identity. The general URI specification of the IETF (Internet Engineering Task Force) is known as RFC2396. URLs (or Uniform Resource Locators) are a subset of URI that specifically identify resources by using their network ’location’ rather than identifying the resource by name or by other attributes. The Semantic Web would be impossible without global identification and hence the use of URIs. The future expansion of URIs into IRIs will ensure that a resource can be identified across language and character encoding boundaries and any discussion about ’meaning’ has to uniquely identify the objects or resources of the discussion.


Layer 2

Layer 2 comprises of Namespaces, XML (Extensible Markup Language) and XML Schema technologies (Figure 1). The function of these technologies is to provide a self-describing syntax for the upper layer language technologies. We acknowledge the existence of DTD (Document Type Declaration) as XML originally used DTD as a validation mechanism, however, DTD was replaced by XML Schema and a discussion of DTD is thus excluded.

Namespaces: Namespaces (NS) provide a simple method for qualifying element and attribute names used in XML (Extensible Markup Language) documents. Namespaces are identified by URI references. The W3C Namespace Recommendation [16] defines an XML namespace as a collection of names, identified by a URI reference [RFC2396], which are used in XML documents as element types and attribute names.

XML: XML (Extensible Markup Language) specifies a standard for the exchange of data over networks, notably the Web. XML is considered to be both a metalanguage and a markup language. XML as metalanguage allows for the specification of the content of documents according to a predefined and specific structure. All documents conforming to this specification will have the same structure or represent data items in the specified structure. In addition, XML as markup language allows for the insertion of markup tags into text to define the logical structure of a document, or to add information regarding information contained in a document (metadata).

An XML document is a text document which in itself does not have any functionality. It is used only to describe data, information or metadata. Thus, XML is a mean for defining common grammars to enable data exchange. It does not specify semantics; all parties must agree on the data model and document structure for XML data exchange to be successful. If an XML grammar is accepted as a standard for data exchange, any XML parser can parse the XML data and access the content if it is a valid XML document. It is however difficult to re-engineer the data model from any given XML document if the document type specification is not available.

XML Schema: An XML schema is an XML document defining the content and structure of one or more derived XML documents. Generally, a schema is a model for describing the structure and content of data. XML Schema is a content modeling language as well as an application of XML that applies only to XML-related languages and documents. In particular, an XML Schema describes a model for a whole class of XML documents. The model describes the possible arrangement of elements, their attributes and text that would be present in a schema-valid document.


Layer 3

RDF (Resource Descriptive Framework) and RDF Schema technologies reside on Layer 3 (refer to Figure 1). The function of these technologies is to provide a metadata description mechanism for the upper language technologies.

RDF: The purpose of RDF (Resource Description Framework) is to declare metadata that is machine-readable,. RDF provides a mechanism to declare statements that describe resources by means of a basic data model. A statement describes an entity (resource) in terms of properties, which have values. Furthermore, an RDF statement is a [subject – predicate - object]. The subject is the resource of the statement. The predicate is the property or characteristic of the subject specified by the statement (examples include creator, creation-date, or language), and the value of the property is the object. In terms of the Semantic Web, the basic object-attribute-value data model is the only semantics prescribed in the RDF specifications. RDF has no other data-modeling

A Semantic Web Status Model 5 commitments specifies no reserved terms for further data modeling or no other mechanisms for declaring property names. For semantic interoperability RDF has significant advantages over XML primarily because of the data model used.


RDF Schema: RDF Schema specifies extensions to RDF that are used to define the common vocabularies in RDF metadata statements. RDF itself provides the data model and does not prescribe any application-specific classes and properties. This is accomplished by RDF Schema. RDF Schema provides a predefined, basic type system for RDF models, thus extending RDF by assigning an externally specified semantics to specific resources. RDF Schema expressions are valid RDF expressions, and therefore RDF Schema is a semantic extension of RDF Software that can interpret RDF can also be used to interpret an RDF Schema implementation; although it will not attach the intended meaning to the built-in schema definitions.

The RDF vocabulary description strategy contained in RDF Schema acknowledges that there are many techniques that enable description of meaning of classes and properties. To extend the description of meaning, ontology languages (such as DAML+OIL, OIL and OWL), inference rule languages and other formalisms are used.



Layer 4

In Figure 1 ’Ontology vocabulary’ is depicted on Layer 4. Here the terminology differs from the three preceding layers, because the functionality rather than the technology is mentioned. OWL is the W3C technology representing this layer. Ontology Vocabulary: specifies a machine readable vocabulary in computer systems technology descriptions. Ontologies assist in creating a common understanding for communication between people and computer applications. Generally it is defined as a shared, formal, explicit specification or conceptualization of a particular domain. Furthermore, ontology is a knowledge representation language capturing the syntax (ontology vocabulary) as well as the semantics (logic language) of a specific domain,

It is envisioned that ontologies will play a crucial role in knowledge processing, sharing, and reuse between Web applications. On the Semantic Web, ontologies may be used in applications required to search across, or merge information from diverse communities.

In early 2001 the W3C initiated a Web-Ontology Working Group (WebOnt) in order to consolidate existing Web ontology efforts (notably OIL and DAML+OIL) into a Web Ontology Language. OWL extends RDF Schema in order to express complex relationships between different classes specified in RDF Schema, as well as to enhance the specification of constraints applicable to classes and properties. OWL specifies three sub-languages of increasing expressiveness. These language are OWL Lite, OWL DL and OWL Full. Ontology designers should select the most appropriate version.



 Layer 5

The Semantic Web model depicts the ’Logic’ layer as being above the ’Ontology vocabulary’ layer. Logic or semantic descriptions are generally included in the specification of a knowledge representation language. Such languages are required to capture ontologies, as ontology typically specifies a domain concept hierarchy. A knowledge representation language is specified when both the syntax and the semantics of the language is described. In the syntax definition, the legal statements in the language are defined (using an ontology vocabulary), and the semantic description specifies the intended meaning of each legal statement.

Logic: The OWL language provides a specific subset in the form of OWL DL to support existing DL (Description Logics) and to provide a language subset that possesses the computational properties required for reasoning systems. DL is a set of knowledge representation formalisms with semantic characterization based on standard first-order logics. DL offers a formal foundation for frame-based systems, where meaning is provided by interpretations that define the formal semantics of the logic




Layer 6

Proof: ’Proof’ as concept exists within the theorem proving domain, for instance as applied in artificial intelligence.. To support Semantic Web proof scenarios, proof languages were developed. A proof language determines the validity of a specific statement. An instance thereof generally consists of a list of inference items used to derive the information in question, as well as the associated trust information of each item.

A Semantic Web will probably not require proof generation and in general proof validation will be adequate. The search for and generating a proof for an arbitrary question, is typically an intractable process for many real world problems, and the Semantic Web does not require this to be solved. For perceived Semantic Web applications construction of a proof is performed according to constrained rules, and only the validation thereof is required from other parties. For example, when a user is granted access to a Web site, an accompanying document explains to the web server why they should be granted access. Such proof for example, could be a chain of assertions and reasoning rules with pointers to all supporting material.



Layer 7

Trust: Semantic Web interaction requires different collaborators to communicate, implying that they have to determine how to trust one another, as well as how to establish the trust levels of acquired information. When dealing with user interactions on the Web, McKnight et. Al defined the term trust as the belief that another entity is benevolent, competent, honest, or predictable in a given situation. Trust also includes the participants’ willingness to depend on one another in a specific interaction. Furthermore, user trust of Semantic Web information is determined by the source of the information, in particular its authenticity and trustworthiness.

Within the Semantic Web the concepts trust and proof are dependent on the interaction context. However, an all-encompassing definition of context is problematic. An appropriate meaning of context is therefore explicated by means of the following example: A user on the Semantic Web receives data from a friend regarding the best music performances. The data can be trusted as it originates from a known (implying verified) friend, whose musical interests are familiar. It is thus possible to use the data because the user either shares or disagrees with the musical tastes of the friend. Within the domain of the Semantic Web, context therefore assists applications or users regarding the trustworthiness and usefulness of data



Digital Signatures

    In the Semantic Web model of Berners-Lee ’Digital Signature’ is associated with the middle four layers. The Digital Signature Standard (DSS) is a cryptographic standard or a particular application of public key cryptography promulgated by NIST (National Institute of Standards and Technology)

    A digital signature (not to be confused with a digital certificate) is an electronic signature that can be used to authenticate identity. Digital signatures are easily transportable, cannot be imitated by someone else, and can be automatically time-stamped. A digital signature can be used with any kind of message, whether it is encrypted or not. A digital certificate contains the digital signature of the certificate issuing authority so that anyone can verify that the certificate is real.

On the Semantic Web a digital signature is a mechanism used to unambiguously verify an identity such as the author of a document. XML signatures are digital signatures designed for use in XML transactions. The implementation of digital signatures on the Semantic Web could result in a system which can express and reason about relationships across the whole range of public-key based security and trust systems.





II- The Seven Layers OSI Model

Sources: OSI Model, from Wikipedia; The 7 Layers of OSI Model, from Webopedia;


 osi model

Source: GlobalKnowing.com, from its OSI Model White Paper


    OSI Reference Model stands for Open Systems Interconnection Reference Model, an abstract description for layered man-machine communication. In its basic form it splits its architecture into seven layers, from top to bottom: the Application, Presentation, Session, Transport, Network, Data-Link, and Physical Layers.

    A layer is a collection of conceptually similar functions that provide services to the layer above it and receives service from the layer below it. For example, a layer that provides error-free communications across a network provides the path needed by applications above it, while it calls the next lower layer to send and receive packets that make up the contents of the path.


7. Application Layer, the first (sending) or last(receiving) layer of a man-machine communication, in fact the closest to the end user. Examples: Telnet,  FTP downloads and uploads; The POP3 process for email reception: a SMTP, Simple Mail Transfer Protocol; A Web page as “seen” by the HTTP protocol;


6. Presentation Layer, where code conversions are performed. It is also known as the Syntax Layer. Examples: EBCDIC to ASCII; Data marking and serializing objects, and/or encapsulations tasks previously to packet sending;


5. Session Layer, where connectivity and machines dialog is established. It is the layer responsible of the “graceful closing” of a session.  Examples: full duplex, half duplex, or simplex; negotiations control of operations such as: updating; adjustments, restart procedures, repetitions, terminations, asking permissions, etc.


4. Transportation Layer, providing the necessary data transparency between users, segmentation control, errors handling and control of missing and rest of messages transmission. Examples: TCP Transfer Control Protocol and UDO, User Datagram Protocol. Their tasks are comparable to the ones of a conventional Post Office.


3. Network Layer, executes under its control variable length data sequences transmissions towards their destinies thru one or more networks. It also controls the whole quality of this service. It is the layer where routing, fragmentation and data assembly tasks are performed reporting errors whether existent. The best example of this complex function is the IP, Internet Protocol where data packages are fragmented as a function of the accessibility and bandwidths at hand.


2. Data Link Layer provides all means to internetworking data transmission, detecting and whether possible correcting errors generated in or by the inferior layer. Examples: A point to point connection between LAN’s or WAN’s.


1. Physical Layer, where all physical and electrical specification of all devices participating in the transmission, are matched and coordinated namely pins, voltages, wire and wiring specifications, hubs, network adapters, buses adapters, etc. It takes care of analog to digital and reverse conversions, modulation and demodulation, digital representations, analog converters, etc.









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Poll Darwin

Darwin puede ser usado para


Poll Semántico I

La Semántica es la

Poll Semántico II

La Web Semántica es una

Poll Semántico III

El Conocimiento Humano es:

Poll Semántico IV

El Tesauro Web es

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