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From Logic to Ontology: The limit of “The Semantic Web”

 

 

(Some post are written in English and Spanish language) 

http://www.linkedin.com/answers/technology/web-development/TCH_WDD/165684-18926951 

From Logic to Ontology: The limit of “The Semantic Web” 

 http://en.wikipedia.org/wiki/Undecidable_problem#Other_problems

If you read the next posts on this blog: 

Semantic Web

The Semantic Web

What is the Semantic Web, Actually?

The Metaweb: Beyond Weblogs. From the Metaweb to the Semantic Web: A Roadmap

Semantics to the people! ontoworld

What’s next for the Internet

Web 3.0: Update

How the Wikipedia 3.0: The End of Google? article reached 2 million people in 4 days!

Google vs Web 3.0

Google dont like Web 3.0 [sic] Why am I not surprised?

Designing a better Web 3.0 search engine

From semantic Web (3.0) to the WebOS (4.0)

Search By Meaning

A Web That Thinks Like You

MINDING THE PLANET: THE MEANING AND FUTURE OF THE SEMANTIC WEB

The long-promised “semantic” web is starting to take shape

Start-Up Aims for Database to Automate Web Searching

Metaweb: a semantic wiki startup

http://www.freebase.com/

The Semantic Web, Collective Intelligence and Hyperdata.

Informal logic 

Logical argument

Consistency proof 

Consistency proof and completeness: Gödel’s incompleteness theorems

Computability theory (computer science): The halting problem

Gödel’s incompleteness theorems: Relationship with computability

Non-formal or Inconsistency Logic: LACAN’s LOGIC. Gödel’s incompleteness theorems,

You will realize the internal relationship between them linked from Logic to Ontology.  

I am writing from now on an article about the existence of the semantic web.  

I will prove that it does not exist at all, and that it is impossible to build from machines like computers.  

It does not depend on the software and hardware you use to build it: You cannot do that at all! 

You will notice the internal relations among them, and the connecting thread is the title of this post: “Logic to ontology.”   

I will prove that there is no such construction, which can not be done from the machines, and that does not depend on the hardware or software used.  

More precisely, the limits of the semantic web are not set by the use of machines themselves and biological systems could be used to reach this goal, but as the logic that is being used to construct it does not contemplate the concept of time, since it is purely formal logic and metonymic lacks the metaphor, and that is what Gödel’s theorems remark, the final tautology of each construction or metonymic language (mathematical), which leads to inconsistencies. 

This consistent logic is completely opposite to the logic that makes inconsistent use of time, inherent of human unconscious, but the use of time is built on the lack, not on positive things, it is based on denials and absences, and that is impossible to reflect on a machine because of the perceived lack of the required self-awareness is acquired with the absence.  

The problem is we are trying to build an intelligent system to replace our way of thinking, at least in the information search, but the special nature of human mind is the use of time which lets human beings reach a conclusion, therefore does not exist in the human mind the halting problem or stop of calculation.  

So all efforts faced toward semantic web are doomed to failure a priori if the aim is to extend our human way of thinking into machines, they lack the metaphorical speech, because only a mathematical construction, which will always be tautological and metonymic, and lacks the use of the time that is what leads to the conclusion or “stop”.  

As a demonstration of that, if you suppose it is possible to construct the semantic web, as a language with capabilities similar to human language, which has the use of time, should we face it as a theorem, we can prove it to be false with a counter example, and it is given in the particular case of the Turing machine and “the halting problem”.  

Then as the necessary and sufficient condition for the theorem is not fulfilled, we still have the necessary condition that if a language uses time, it lacks formal logic, the logic used is inconsistent and therefore has no stop problem.

This is a necessary condition for the semantic web, but it is not enough and therefore no machine, whether it is a Turing Machine, a computer or a device as random as a black body related to physics field, can deal with any language other than mathematics language hence it is implied that this language is forced to meet the halting problem, a result of Gödel theorem.   

De la lógica a la ontología: El límite de la “web semántica”  

Si lee los siguientes artículos de este blog: 

http://es.wikipedia.org/wiki/Web_sem%C3%A1ntica  

Wikipedia 3.0: El fin de Google (traducción Spanish)

Lógica 

Lógica Consistente y completitud: Teoremas de la incompletitud de Gödel (Spanish)

Consistencia lógica (Spanish)

Teoría de la computabilidad. Ciencia de la computación.

Teoremas de la incompletitud de Gödel y teoría de la computación: Problema de la parada 

Lógica inconsistente e incompletitud: LOGICAS LACANIANAS y Teoremas de la incompletitud de Gödel (Spanish)  

Jacques Lacan (Encyclopædia Britannica Online)

Usted puede darse cuenta de las relaciones internas entre ellos, y el hilo conductor es el título de este mismo post: “de la lógica a la ontología”.  

Probaré que no existe en absoluto tal construcción, que no se puede hacer desde las máquinas, y que no depende ni del hardware ni del software utilizado.   

Matizando la cuestión, el límite de la web semántica está dado no por las máquinas y/o sistemas biológicos que se pudieran usar, sino porque la lógica con que se intenta construir carece del uso del tiempo, ya que la lógica formal es puramente metonímica y carece de la metáfora, y eso es lo que marcan los teoremas de Gödel, la tautología final de toda construcción y /o lenguaje metonímico (matemático), que lleva a contradicciones.  

Esta lógica consistente es opuesta a la lógica inconsistente que hace uso del tiempo, propia del insconciente humano, pero el uso del tiempo está construido en base a la falta, no en torno a lo positivo sino en base a negaciones y ausencias, y eso es imposible de reflejar en una máquina porque la percepción de la falta necesita de la conciencia de sí mismo que se adquiere con la ausencia.   

El problema está en que pretendemos construir un sistema inteligente que sustituya nuestro pensamiento, al menos en las búsquedas de información, pero la particularidad de nuestro pensamiento humano es el uso del tiempo el que permite concluir, por eso no existe en la mente humana el problema de la parada o detención del cálculo, o lo que es lo mismo ausencia del momento de concluir.  

Así que todos los esfuerzos encaminados a la web semántica están destinados al fracaso a priori si lo que se pretende es prolongar nuestro pensamiento humano en las máquinas, ellas carecen de discurso metafórico, pues sólo son una construcción matemática, que siempre será tautológica y metonímica, ya que además carece del uso del tiempo que es lo que lleva al corte, la conclusión o la “parada”.  

Como demostración vale la del contraejemplo, o sea que si suponemos que es posible construir la web semántica, como un lenguaje con capacidades similares al lenguaje humano, que tiene el uso del tiempo, entonces si ese es un teorema general, con un solo contraejemplo se viene abajo, y el contraejemplo está dado en el caso particular de la máquina de Turing y el “problema de la parada”.  

Luego no se cumple la condición necesaria y suficiente del teorema, nos queda la condición necesaria que es que si un lenguaje tiene el uso del tiempo, carece de lógica formal, usa la lógica inconsistente y por lo tanto no tiene el problema de la parada”, esa es condición necesaria para la web semántica, pero no suficiente y por ello ninguna máquina, sea de Turing, computador o dispositivo aleatorio como un cuerpo negro en física, puede alcanzar el uso de un lenguaje que no sea el matemático con la paradoja de la parada, consecuencia del teorema de Gödel.

Jacques Lacan (Encyclopædia Britannica Online)

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Semantic Web

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Semantic Web

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The Semantic Web is an evolving extension of the World Wide Web in which web content can be expressed not only in natural language, but also in a format that can be read and used by software agents, thus permitting them to find, share and integrate information more easily.[1] It derives from W3C director Tim Berners-Lee‘s vision of the Web as a universal medium for data, information, and knowledge exchange.

At its core, the semantic web is comprised of a philosophy,[2] a set of design principles,[3] collaborative working groups, and a variety of enabling technologies. Some elements of the semantic web are expressed as prospective future possibilities that have yet to be implemented or realized.[4] Other elements of the semantic web are expressed in formal specifications.[5] Some of these include Resource Description Framework (RDF), a variety of data interchange formats (e.g. RDF/XML, N3, Turtle, N-Triples), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL), all of which are intended to provide a formal description of concepts, terms, and relationships within a given knowledge domain.

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[edit] Purpose

Humans are capable of using the Web to carry out tasks such as finding the Finnish word for “car,” to reserve a library book, or to search for the cheapest DVD and buy it. However, a computer cannot accomplish the same tasks without human direction because web pages are designed to be read by people, not machines. The semantic web is a vision of information that is understandable by computers, so that they can perform more of the tedious work involved in finding, sharing and combining information on the web.

For example, a computer might be instructed to list the prices of flat screen HDTVs larger than 40 inches (1,000 mm) with 1080p resolution at shops in the nearest town that are open until 8pm on Tuesday evenings. Today, this task requires search engines that are individually tailored to every website being searched. The semantic web provides a common standard (RDF) for websites to publish the relevant information in a more readily machine-processable and integratable form.

Tim Berners-Lee originally expressed the vision of the semantic web as follows[6]:

I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.

Tim Berners-Lee, 1999

Semantic publishing will benefit greatly from the semantic web. In particular, the semantic web is expected to revolutionize scientific publishing, such as real-time publishing and sharing of experimental data on the Internet. This simple but radical idea is now being explored by W3C HCLS group’s Scientific Publishing Task Force.

Tim Berners-Lee has further stated[7]:

People keep asking what Web 3.0 is. I think maybe when you’ve got an overlay of scalable vector graphics – everything rippling and folding and looking misty – on Web 2.0 and access to a semantic Web integrated across a huge space of data, you’ll have access to an unbelievable data resource.

Tim Berners-Lee, A ‘more revolutionary’ Web

[edit] Relationship to the Hypertext Web

[edit] Markup

Many files on a typical computer can be loosely divided into documents and data. Documents, like mail messages, reports and brochures, are read by humans. Data, like calendars, addressbooks, playlists and spreadsheets, are presented using an application program which lets them be viewed, searched and combined in many ways.

Currently, the World Wide Web is based mainly on documents written in Hypertext Markup Language (HTML), a markup convention that is used for coding a body of text interspersed with multimedia objects such as images and interactive forms. Metadata tags, for example <meta name="keywords" content="computing, computer studies, computer"><meta name="description" content="xxxx... "><meta name="author" content="xxxx"> provide a method by which computers can catagorise the content of web pages.

The semantic web takes the concept further; it involves publishing the data in a language, Resource Description Framework (RDF), specifically for data, so that it can be categorized as human perception and be “understood” by computers. So the data are not just stored but filed and well handled.

HTML describes documents and the links between them. RDF, by contrast, describes arbitrary things such as people, meetings, or airplane parts.

For example, with HTML and a tool to render it (perhaps Web browser software, perhaps another user agent), one can create and present a page that lists items for sale. The HTML of this catalog page can make simple, document-level assertions such as “this document’s title is ‘Widget Superstore’”. But there is no capability within the HTML itself to assert unambiguously that, for example, item number X586172 is an Acme Gizmo with a retail price of €199, or that it is a consumer product. Rather, HTML can only say that the span of text “X586172″ is something that should be positioned near “Acme Gizmo” and “€ 199″, etc. There is no way to say “this is a catalog” or even to establish that “Acme Gizmo” is a kind of title or that “€ 199″ is a price. There is also no way to express that these pieces of information are bound together in describing a discrete item, distinct from other items perhaps listed on the page.

See also: Semantic HTML, Linked Data.

[edit] Descriptive and extensible

The semantic web addresses this shortcoming, using the descriptive technologies Resource Description Framework (RDF) and Web Ontology Language (OWL), and the data-centric, customizable Extensible Markup Language (XML). These technologies are combined in order to provide descriptions that supplement or replace the content of Web documents. Thus, content may manifest as descriptive data stored in Web-accessible databases, or as markup within documents (particularly, in Extensible HTML (XHTML) interspersed with XML, or, more often, purely in XML, with layout/rendering cues stored separately). The machine-readable descriptions enable content managers to add meaning to the content, i.e. to describe the structure of the knowledge we have about that content. In this way, a machine can process knowledge itself, instead of text, using processes similar to human deductive reasoning and inference, thereby obtaining more meaningful results and facilitating automated information gathering and research by computers.

[edit] Skeptical reactions

[edit] Practical feasibility

Some critics question the basic feasibility of a complete or even partial fulfillment of the semantic web. Some develop their critique from the perspective of human behavior and personal preferences, which ostensibly diminish the likelihood of its fulfillment (see e.g., metacrap). Other commentators object that there are limitations that stem from the current state of software engineering itself. (see e.g., Leaky abstraction).

Where semantic web technologies have found a greater degree of practical adoption, it has tended to be among core specialized communities and organizations for intra company projects.[8] The practical constraints toward adoption have appeared less challenging where domain and scope is more limited than that of the general public and the world wide web.[8]

[edit] An unrealized idea

The original 2001 Scientific American article (from Berners-Lee) described an expected evolution of the existing Web to a Semantic Web. Such an evolution has yet to occur. Indeed, a more recent article from Berners-Lee and colleagues stated that: “This simple idea, however, remains largely unrealized.” [9] Nonetheless, the recognized authorities in the Semantic Web keep asserting the feasibility of the original idea, and sometimes they even claim that many of the components of the initial vision have already been deployed.[citation needed]

[edit] Censorship and privacy

Enthusiasm about the semantic web could be tempered by concerns regarding censorship and privacy. For instance, text-analyzing techniques can now be easily bypassed by using other words, metaphors for instance, or by using images in place of words. An advanced implementation of the semantic web would make it much easier for governments to control the viewing and creation of online information, as this information would be much easier for an automated content-blocking machine to understand. In addition, the issue has also been raised that, with the use of FOAF files and geo location meta-data, there would be very little anonymity associated with the authorship of articles on things such as a personal blog.

[edit] Doubling output formats

Another criticism of the semantic web is that it would be much more time-consuming to create and publish content because there would need to be two formats for one piece of data: one for human viewing and one for machines. However, many web applications in development are addressing this issue by creating a machine-readable format upon the publishing of data or the request of a machine for such data. The development of microformats has been one reaction to this kind of criticism.

Specifications such as eRDF and RDFa allow arbitrary RDF data to be embedded in HTML pages. The GRDDL (Gleaning Resource Descriptions from Dialects of Language) mechanism allows existing material (including microformats) to be automatically interpreted as RDF, so publishers only need to use a single format, such as HTML.

[edit] Components

[edit] XML, XML Schema, RDF, OWL, SPARQL

The semantic web comprises the standards and tools of XML, XML Schema, RDF, RDF Schema and OWL. The OWL Web Ontology Language Overview describes the function and relationship of each of these components of the semantic web:

  • XML provides an elemental syntax for content structure within documents, yet associates no semantics with the meaning of the content contained within.
  • XML Schema is a language for providing and restricting the structure and content of elements contained within XML documents.
  • RDF is a simple language for expressing data models, which refer to objects (“resources“) and their relationships. An RDF-based model can be represented in XML syntax.
  • RDF Schema is a vocabulary for describing properties and classes of RDF-based resources, with semantics for generalized-hierarchies of such properties and classes.
  • OWL adds more vocabulary for describing properties and classes: among others, relations between classes (e.g. disjointness), cardinality (e.g. “exactly one”), equality, richer typing of properties, characteristics of properties (e.g. symmetry), and enumerated classes.
  • SPARQL is a protocol and query language for semantic web data sources.

Current ongoing standardizations include:

The intent is to enhance the usability and usefulness of the Web and its interconnected resources through:

  • servers which expose existing data systems using the RDF and SPARQL standards. Many converters to RDF exist from different applications. Relational databases are an important source. The semantic web server attaches to the existing system without affecting its operation.
  • documents “marked up” with semantic information (an extension of the HTML <meta> tags used in today’s Web pages to supply information for Web search engines using web crawlers). This could be machine-understandable information about the human-understandable content of the document (such as the creator, title, description, etc., of the document) or it could be purely metadata representing a set of facts (such as resources and services elsewhere in the site). (Note that anything that can be identified with a Uniform Resource Identifier (URI) can be described, so the semantic web can reason about animals, people, places, ideas, etc.) Semantic markup is often generated automatically, rather than manually.
  • common metadata vocabularies (ontologies) and maps between vocabularies that allow document creators to know how to mark up their documents so that agents can use the information in the supplied metadata (so that Author in the sense of ‘the Author of the page’ won’t be confused with Author in the sense of a book that is the subject of a book review).
  • automated agents to perform tasks for users of the semantic web using this data
  • web-based services (often with agents of their own) to supply information specifically to agents (for example, a Trust service that an agent could ask if some online store has a history of poor service or spamming).

[edit] Projects

[edit] Neurocommons

The Neurocommons is an open RDF database developed by Science Commons. It was compiled from major life sciences databases with a focus on neuroscience. It is accessible via a web-based front end using the SPARQL query language at its original location trieu and at the DERI mirror location.

[edit] FOAF

A popular application of the semantic web is Friend of a Friend (or FoaF), which describes relationships among people and other agents in terms of RDF.

[edit] SIOC

The SIOC Project – Semantically-Interlinked Online Communities provides a vocabulary of terms and relationships that model web data spaces. Examples of such data spaces include, among others: discussion forums, weblogs, blogrolls / feed subscriptions, mailing lists, shared bookmarks, image galleries.

[edit] SIMILE

Semantic Interoperability of Metadata and Information in unLike Environments Massachusetts Institute of Technology

SIMILE is a joint project, conducted by the MIT Libraries and MIT CSAIL, which seeks to enhance interoperability among digital assets, schemata/vocabularies/ontologies, meta data, and services.

[edit] Linking Open Data

 linking-open-data-diagram_2007-09.jpg

Datasets in the Linking Open Data project, as of September 2007

The Linking Open Data project is a community lead effort to create openly accessible, and interlinked, RDF Data on the Web. The data in question takes the form of RDF Data Sets drawn from a broad collection of data sources. There is a focus on the Linked Data style of publishing RDF on the Web.

The project is one of several sponsored by the W3C‘s Semantic Web Education & Outreach Interest Group (SWEO)

[edit] Tools

[edit] Browsers

A semantic web Browser is a form of Web User Agent that expressly requests RDF data from Web Servers using the best practice known as “Content Negotiation”. These tools provide a user interface that enables data-link oriented navigation of RDF data by dereferencing the data links (URIs) in the RDF Data Sets returned by Web Servers.

Examples of semantic web browsers include:

[edit] Services

[edit] Notification Services

[edit] Semantic Web Ping Service

The Semantic Web Ping Service is a notification service for the semantic web that tracks the creation and modification of RDF based data sources on the Web. It provides Web Services for loosely coupled monitoring of RDF data. In addition, it provides a breakdown of RDF data sources tracked by vocabulary that includes: SIOC, FOAF, DOAP, RDFS, and OWL.

[edit] Piggy Bank

Another freely downloadable tool is the plug-in to Firefox, Piggy Bank. Piggy Bank works by extracting or translating web scripts into RDF information and storing this information on the user’s computer. This information can then be retrieved independently of the original context and used in other contexts, for example by using Google Maps to display information. Piggy Bank works with a new service, Semantic Bank, which combines the idea of tagging information with the new web languages. Piggy Bank was developed by the Simile Project, which also provides RDFizers, tools that can be used to translate specific types of information, for example weather reports for US zip codes, into RDF. Efforts like these could ease a potentially troublesome transition between the web of today and its semantic successor.

[edit] See also

Concepts and methodologies
Related articles
Companies and applications

[edit] References

  • Cardoso, J. (March 2007). Semantic Web Services: Theory, Tools and Applications. Idea Group.. ISBN 978-1-59904-045-5. 
  • Cardoso, J., Sheth, Amit (2006). Semantic Web Services, Processes and Applications. Springer. ISBN 0-38730239-5. 
  • Jane Greenberg, Eva Mendez (Eds.) (2007). Knitting the Semantic Web. New York: The Haworth Information Press. ISBN 0-7890-3591-2. 

[edit] Notes

  1. ^ http://www.w3.org/2001/sw/SW-FAQ#What1
  2. ^ http://www.w3.org/2001/sw/Activity
  3. ^ http://www.w3.org/DesignIssues/
  4. ^ http://www.w3.org/2001/sw/SW-FAQ#What3
  5. ^ http://www.w3.org/2001/sw/#spec
  6. ^ Berners-Lee, Tim; Fischetti, Mark (1999). Weaving the Web. HarperSanFrancisco, chapter 12. ISBN 9780062515872. 
  7. ^ Victoria Shannon (2006-06-26). A ‘more revolutionary’ Web. International Herald Tribune. Retrieved on 2006-05-24.
  8. ^ a b Ivan Herman (2007). State of the Semantic Web. Semantic Days 2007. Retrieved on 2007-07-26.
  9. ^ Nigel Shadbolt, Wendy Hall, Tim Berners-Lee (2006). The Semantic Web Revisited. IEEE Intelligent Systems. Retrieved on 2007-04-13.

[edit] External links

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 Application Development

SPARQL Will Make the Web Shine
By Jim Rapoza

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