lunes, 27 de julio de 2009

La Web Semántica

Este documento ha sido pensado para ser una sencilla pero comprensiva publicacion para para calquiera que desee introducirse en la Web Semantica: desde principiantes hasta hackers experimentados. Lectura previa recomendada: the Semantic Web in Breadth (Boquejo de la Web Semantica).

Tabla de Contenidos

  1. Que es la Web Semantica?
  2. Disenho de Datos con Schemata
  3. Ontologias, Inferencias y DAML
  4. El poder de los Lenguages de la Web Semantica
  5. Autenticidad y comprobacion
  6. Informacion Ambiental y SEM
  7. Evolucion
  8. Funciona? Que aplicaciones de la Web Semantica existen?
  9. Enlaces relacionados

Que es la Web Semantica?

La Web Semantica es una malla de informacion relacionada de una forma que sea facilmente procesable por los ordenadores a una escala global. Puede pensarse como una forma de representar eficientemente datos en Internet o una base de datos globalmente relacionada.

La Web Semantica fue una idea de Tim Berners-Lee, inventor de la WWW, URIs, HTTP y HTML. Hay un equipo de gente en el World Wide Web Consortium (W3C) dedicada a mejorar, extender y estandarizar el sistema y muchos lenguages, publicaciones y herramientas han sido ya desarrollados. A pesar de ello, las tecnologias de la Web Semantica aun estan en estado muy temprano, y aunque el futuro de proyecto eb general parece ser brillante, parece haber poco consenso sobre la direccion que debe tomar y las caracteristicas de los comienzos de la Web Semantica.

En que se basa este sistema? Los datos, generalmente ocultos en archivos HTML, suelen er utiles en algunos contextoss, pero no en otros. El problema con la mayoria de los datos en la Web de esta forma es que es dificil de usar en una larga escala, porque no hay un sistema global para publicar datos de tal forma que pueda ser facilmente procesada por cualquiera. Por ejemplo, simplente piensa sobre la informacion sobre eventos locales deportivos, informacion del tiempo, horarios de aviones, estadisticas de la Liga de Beibol, y guias de television... toda esta informacion se muetra en muchos sitios, pero toda en HTML. El problema es que, en algunos contextos, es dificil uar eta data en las formas que nosotros quisieramos.

Asi la Web Semantica puede ser vista como una gran obra de ingenieria... pero es mas que eso. Descubriremos que se hace mas sencillo publicar datos en un repurposable form, asi que mas gente querra publicar datos, y habra un knock-on o fecto domino. Podremos encontrar que un gran numero de aplicaciones de la Web Semantica pueden ser usadas para varias tareas, incrementando la modularidad de las aplicaciones en la Web. Pero ya basta de razonamientos subjetivos... sobre como esto sera cumplido.

La Web Semantica se construye generalmente en sintaxis que utilizan URIs (Idenficiadores Uniformes de Recursos) para representar los datos, generalmente en estructoras basada en triplete: p.ej. mucho tripletes de datos URI que pueden ser almacenados en bases de datos, o intercambiados en la World Wide Web usando ciertas sintaxis dienhadas especificamente para la tarea. Estas sintaxis de llaman "Framework de Descripcion de Recursos" (RDF).

URI - Identificador Uniforme de Recursos

Una URI es simplemente un identificador Web: como las cadenas comenzando por "http:" o "ftp:" que pueden encontrarse usualmente en la World Wide Web. Cualquiera puede crear una URI, y su propiedadad es claramente delegada, asi forman una tecnologia bae ideal sobre la cual puede contruire una Web global. De hecho, la World Wide Web es algo asi: cualquier cosa que tiene una URI se considera estar "en la Web".

La sintaxis de las URIs es cuidadosamente controlada por el IETF, que ha publicado el RFC 2396 como la especificacion general para las URI. EL W3C mantiene una lista de schemas URI.

RDF - Marco de Descripción de Recursos

Un triplete puede ser describido simplemente como tres URIs. Un lengiaje que utiliza tres URIs de tal forma se llama RDF: el W3C ha desarrollamado una serializacion XML para RDF, la "Sintaxis" en la recomendacion para la especificacion del modelo y sintaxis RDF. RDF en XML es considerado el formato de intercambio estandar para RDF en la Web Semantica, aunque no es el unico formato. Por ejemplo, Notation3 (que se tratara mas tarde en este articulo) es una excelente alternativa para este formato en texto plano.

Una vez la informacion esta en formato RDF, e hace mas facil procesarla, ya que RDF es un formato generico, que ya cuenta con muchos conversores. RDF en XML es una especificacion muy detallada, a la que lleva un tiempo acostumbrarse (por ejemplo, para aprender adecuadamente RDF en XML, debera de antemano saber un poco sobre los espacios de nombres en XML...), pero veamo un pequeno ejemplo de RDF en XML ahora mismo:-

   xmlns:dc="http://purl.org/dc/elements/1.1/"
   xmlns:foaf="http://xmlns.com/0.1/foaf/" >
   
       
           Sean B. Palmer
       
       The Semantic Web: An Introduction

Este fragmento de RDF dice basicamente que este articulo tiene el titulo "The Semantic Web: An Introduction" (en su version inglesa), y ha sido escrito por alguien cuyo nombre es "Sean B. Palmer". Aqui estan los tripletes que este RDF produce:-

<>  _:x0 .
this  "The Semantic Web: An Introduction" .
_:x0  "Sean B. Palmer" .

Este formato es realmente serializacion de RDF en texto plano llamada "Notation3", que eta tratada mas adelante. Fijese que algunas personas actualmente prefieren usar RDF en XML a Notation3, pero es generalmente aceptado que Notation3 es mas facil de usar, y por supuesto se puede convertir a RDF en XML igualmente.

Por que RDF?

Cuando la gente se enfrenta a RDF en XML por primera vez, generalmente tienen dos preguntas: "Porque usar RDF en vez de XML?", y "utiliza un Schema XML en conjunto con RDF?".

La respuesta a la primera pregunta es bastante sencilla, and is por doble partida. Primeramente, el beneficio que uno obtiene de disenhar un enguaje en RDF es que los mapea la informacion directamente y sin lugar a dudas a un modelo, el cual es descentralizado, y para el cual hay muchos conversores ya disponibles. Esto significa que si tienes una aplicacion RDF, sabras cuales bits de datos son la semantica de la aplicacion, y cuales son simplemente envoltorio. Y no solo eso, todo el mundo lo sabe, muchas veces incluso sin leer la especificiacion ya que RDF es tan bien conocido. La segunda parte es que esperamos que los datos en RDF formen parte de la Web Semantica, asi los beneficios de disenhar tus datos en RDF ahora tiene paralismo con disenhar tu informacion en HTML en los dias tempranos de la Web.

La respuesta a "Usamos el Schema XML en conjunto con RDF?" lo es tanto como corta. El Schema XML es is a language for restricting the syntax of XML applications. RDF already has a built in BNF that sets out how the language is to be used, so on the face of it the answer is a solid "no". However, using XML Schema in conjunction with RDF may be useful for creating datatypes and so on. Therefore the answer is "possibly", with a caveat that it is not really used to control the syntax of RDF. This is a common misunderstanding, perpetuated for too long now.

Abandono de la pantalla, y formularios

Para que la Web Semantica alcance todo su potencial, mucha gente debe empezar a publicar datos en formato RDF. De donde provendra toda esta informacion? Mucha puede derivarse de fuentes de datos que existen actualmente, utilizando un proceso llamado "abandono de la pantalla". El Abandono de la Pantalla es el acto de literalmente trasladar la informacion desde la fuenta hasta un formato manejable (p.ej. RDF) utilizando lo que mas tengamos a mano. Dos interesantes herramientas para el abandono de la pantalla son XSLT (un lenguaje de transformaciones en XML), y RegExps (en Perl, Python, y demas).

A pesar de ello, el avandono de la pantalla es a menudo una solucion muy tediosa, asiotra forma de afrontarlo es construir propiamente sistemas RDF que tomen la entrada del usuario y lo almacenen directamente en RDF. Datos como los que tu introduces cuando creas una cuenta de correo, compras unos CDs online, o buscas un coche usado pueden ser todos almacenados en RDF y usados en la Web Semantica.

Notation3: El RDF hecho facil

As you will have seen above, XML RDF can be rather difficult, but thankfully, there is are simpler teaching forms of RDF. One of these is called "Notation3", and was developed by Tim Berners-Lee. There is some documentation covering N3, including a specification, and an excellent Primer.

El criterio de diseno tras Notation3 es realmente simple: disenar un sencillo y facil de aprender scribblable formato RDF, sobre el que se pueden construir facilmente aplicaciones y tambien ser transformado. En Notation3, podemos simplemente escribir las URIs en un triplete, delimitadolos con los simbolos "<" y ">". Por ejemplo, aqui observamos un sencillo triplete consistente en tres URIs:-

   .

Para emplear valores literales, simplemente encerrar el valor en comillas dobles, como aqui:-

  "Sean" .

Si desea proveer una URI para algo sobre lo que esta hablando,tambien existe un concepto para ello (es como decir "hay alguien llamado... pero sin asignarle una URI). Simplemente use una linea baja y un colon, y ponga una ai una pequena etiqueta:-

_:a1  "Sean" .

This may be read as "there is something that has the name Sean", or "a1 has the name Sean, for some value of a1". These things are called anonymous nodes, because they don't have a URI, and are sometimes referred to as existentially quantified nodes.

Note how in one of the examples above, we used the URI "http://xyz.org/#" three times, with only the last character changing each time? Notation3 gives us an excellent way to abbreviate this: by giving parts of URIs aliases, and using those aliases instead. This is how you declare an alias in Notation3:-

@prefix xyz:  .

Note that you must always declare an alias before you can use it. To use an alias, simply use the "xyz:" bit instead of the URI, and don't wrap the resulting term in the "<" and ">" delimiters. For example, instead of writing:-

   .

We can instead do:-

@prefix xyz:  .
:a :b :c .

Note that it doesn't matter what alias you use for a URI, as long as you use the same one throughout that document. You can also declare many aliases. The following bits of code are both equivalent to the piece of code above:-

@prefix blargh:  .
blargh:a blargh:b blargh:c .
@prefix blargh:  .
@prefix xyz:  .
blargh:a xyz:b blargh:c .

However, it should be noted that we often use a few aliases pretty much standardly, so that when Semantic Web developers exchange code in plain text, they can just leave the prefixes out and people can guess what they're talking about. Note that code should not implement this feature. Here is an example of some "standard" aliases:-

@prefix : <#> .
@prefix rdf:  .
@prefix rdfs:  .
@prefix daml:  .
@prefix log:  .
@prefix dc:  .
@prefix foaf:  .

The empty alias ":" is often used to denote a new namespace that the author has not yet created a URI for (tut, tut). We use it in this introduction.

Notation3 does have many other little constructs including contexts, DAML lists, and alternative ways of representing anonymous nodes, but we need not concern ourselves with them here. Note that a syntax was devised to be an even simpler subset of Notation3, called N-Triples, but it doesn't use prefixes, and hence many of the examples in this article are not valid N-Triples, but are valid Notation3.

Dan Connolly once called Notation3 a "poor-man's RDF authoring tool" (source: RDF IG logs, 2001-06-01 03:55:12). Apparently, it is called Notation3 because "RDF M&S was the first, the RDF strawman was the second and this is the third" (source: RDF IG F2F 2001-02-26).

CWM: An XML RDF And Notation3 Inference Engine

Although we won't be discussing inference engines until later on in this article, we should note at this point that much RDF and Semantic Web processing (albeit often only experimental or demonstrative, at this stage) is done using a Python program called CWM or "Closed World Machine". More information can be found on the SWAP site.

At the moment, the best demonstration of its use can be how it can convert from XML RDF into Notation3 and vice versa. To convert "a.n3" into "a.rdf", simply use the following command line:-

python cwm.py a.n3 -rdf > a.rdf

CWM es un conjunto de utilidades muy practica para la Web Semantica, nos referiremos a el ocasionalmente en este articulo.

Modelado Sencillo de Datos: Schemata

The first "layer" of the Semantic Web above the syntax discussed above is the simple datatyping model. A "schema" (plural "schemata") is simply a document or piece of code that controls a set of terms in another document or piece of code. It's like a master checklist, or definition grammar.

RDF Schema

RDF Schema (tambien: RDF Schema Candidate Recommendation) was designed to be a simple datatyping model for RDF. Using RDF Schema, we can say that "Fido" is a type of "Dog", and that "Dog" is a sub class of animal. We can also create properties and classes, as well as doing some slightly more "advanced" stuff such as creating ranges and domains for properties.

All of the terms for RDF Schema start with "http://www.w3.org/2000/01/rdf-schema#", which you may have noticed is in our list of "standard" aliases above. The alias "rdfs:" is often used for RDF Schema, and we continue that tradition here.

The first three most important concepts that RDF and RDF Schema give us are the "Resource" (rdfs:Resource), the "Class" (rdfs:Class), and the "Property" (rdf:Property). These are all "classes", in that terms may belong to these classes. For example, all terms in RDF are types of resource. To declare that something is a "type" of something else, we just use the rdf:type property:-

rdfs:Resource rdf:type rdfs:Class .
rdfs:Class rdf:type rdfs:Class .
rdf:Property rdf:type rdfs:Class .
rdf:type rdf:type rdf:Property .

This simply says that "Resource is a type of Class, Class is a type of Class, Property is a type of Class, and type is a type of Property". These are all true statements.

It is quite easy to make up your own classes. For example, let's create a class called "Perro", which contains all of the dogs in the world:-

:Perro rdf:type rdfs:Class .

Ahora podemos decir que" Fido es un tipo de Perro":-

:Fido rdf:type :Perro .

We can also create properties quite easily by saying that a term is a type of rdf:Property, and then use those properties in our RDF:-

:name rdf:type rdf:Property .
:Fido :name "Fido" .

Why have we said that Fido's name is "Fido"? Because the term ":Fido" is a URI, and we could quite easily have chosen any URI for Fido, including ":Squiggle" or ":n508s0srh". We just happened to use the URI ":Fido" because it's easier to remember. However, we still have to tell machines that his name is Fido, because although people can guess that from the URI (even though they probably shouldn't), machines can't.

RDF Schema also has a few more properties that we can make use of: rdfs:subClassOf and rdfs:subPropertyOf. These allow us to say that one class or property is a sub class or sub property of another. For example, we might want to say that the class "Dog" is a sub class of the class "Animal". To do that, we simply say:-

:Perro rdfs:subClassOf :Animal .

Hence, when we say that Fido is a Perro, we are also saying that Fido is an Animal. We can also say that there are other sub classes of Animal:-

:Human rdfs:subClassOf :Animal .
:Pato rdfs:subClassOf :Animal .

And then create new instances of those classes:-

:Bob rdf:type :Humano .
:Quakcy rdf:type :Pato .

And then we can invent another property, use that, and build up even more information...

:owns rdf:type rdf:Property .
:Bob :owns :Fido .
:Bob :owns :Quacky .
:Bob :name "Bob Fleming" .
:Quacky :name "Quakcy" .

And so on. You can see that RDF Schema is very simple, and yet allows one to build up knowledge bases of data in RDF very very quickly.

The next concepts which RDF Schema provides us, which are important to mention, are ranges and domains. Ranges and domains let us say what classes the subject and object of each property must belong to. For example, we might want to say that the property ":bookTitle" must always apply to a book, and have a literal value:-

:Book rdf:type rdfs:Class .
:bookTitle rdf:type rdf:Property .
:bookTitle rdfs:domain :Book .
:bookTitle rdfs:range rdfs:Literal .
:MyBook rdf:type :Book .
:MyBook :bookTitle "My Book" .

rdfs:domain always says what class the subject of a triple using that property belongs to, and rdfs:range always says what class the object of a triple using that property belongs to.

RDF Schema also contains a set of properties for annotating schemata, providing comments, labels, and the like. The two properties for doing this are rdfs:label and rdfs:comment, and an example of their use is:-

:bookTitle rdfs:label "bookTitle";
  rdfs:comment "the title of a book" .

Es una buena practica rtiquetar siempre y comentar tus nuevas propiedades, clases y otros terminos.

Ontologias, Inferencias y DAML

DAML es un lenguage creado por el DARPA como un lenguaje para otologias e inferencias basado en RDF. DAML va mas ala de RDF Schema, ofreciendonos propiedades y clases mas profundas. DAML allows one to be even more expressive than with RDF Schema, and brings us back on track with our Web Semantica discussion by providing some simple terms for creating inferences.

DAML+OIL

DAML provides us a method of saying things such as inverses, unambiguous properties, unique properties, lists, restrictions, cardinalities, pairwise disjoint lists, datatypes, and so on. We shall run through a couple of these here, but armed with the knowledge that you've already gotten from this introduction (assuming that you haven't skipped any of it!), it should be just as beneficial going through the DAML+OIL Walkthru.

One DAML construct that we shall run through is the daml:inverseOf property. Using this property, we can say that one property is the inverse of another. The rdfs:range and rdfs:domain values of daml:inverseOf is rdf:Property. Here is an example of daml:inverseOf being used:-

:hasName daml:inverseOf :isNameOf .
:Sean :hasName "Sean" .
"Sean" :isNameOf :Sean .

La segunda contrucción DAML util que deberiamos mencionar es la clase daml:UnambiguousProperty. Indicando que una Property (Propiedad) es una daml:UnambiguousProperty significa que si el objeto de la propiedad es el mismo, los asuntos son equivalentes. Por ejemplo:-

foaf:mbox rdf:type daml:UnambiguousProperty .
:x foaf:mbox  .
:y foaf:mbox  .

implica que:-

:x daml:equivalentTo :y .

Don't worry if this is getting all a bit too much... it's not essential to learning about the Semantic Web, but it is useful, since many Semantic Web applications now involve DAML. However, DAML is only one in a series of languages and so forth that are being used.

Inferencia

The principle of "inference" is quite a simple one: being able to derive new data from data that you already know. In a mathematical sense, querying is a form of inference (being able to infer some search results from a mass of data, for example). Inference is one of the driving principles of the Semantic Web, because it will allow us to create SW applications quite easily.

To demonstrate the power of inference, we can use some simple examples. Let's take the simple car example: we can say that:-

:MyCar de:macht "160KW" .

Now, to a German Semantic Web processor, the term ":macht" may well be built into it, and although an English processor may have an equivalent term built into it somewhere, it will not understand the code with the term in it that it doesn't understand. Here, then, is a piece of inference data that makes things clearer to the processor:-

de:macht daml:equivalentTo en:power .

We have used the DAML "equivalentTo" property to say that "macht" in the German system is equivalent to "power" in the English system. Now, using an inference engine, a Semantic Web client could successfully determine that:-

:MyCar en:power "160KW" .

This is only a very simple example of inference, but you can see immediately how easily the system could scale up. Merging databases simply becomes a matter of recording in RDF somewhere that "Person Name" in your database is equivalent to "Name" in my database, and then throwing all of the information together and getting a processor to think about it.

Indeed, this is already possible with Semantic Web tools that we have at our disposal today: CWM. Unfortunately, great levels of inference can only be provided using "First Order Predicate Logic" languages, and DAML is not a FOPL language entirely.

Logica

Para que la Web Semantica resulte suficientemente expresiva para ayudarnos en una amplia variedad de situaciones, it will become necessary to construct a powerful logical language for making inferences. There is a raging debate as to how and even whether this can be accomplished, with people pointing out that RDF lacks the power to quantify, and that the scope of quantification is not well defined. Predicate logic is better discussed in John Sowa's excellent Mathematical Background (Predicate Logic).

In particular, Pat Hayes is hard at work on a model for RDF that may ease the situation (2001-09), but there is still a great amount of uncertainty at this time. Of course, this does not stop us from using a Webized version of KIF or somesuch as a logical language on the Semantic Web.

At any rate, we already have a great range of tools with which to build the Semantic Web: assertions (i.e. "and"), and quoting (reification) in RDF, classes, properties, ranges and documentation in RDF Schema, disjoint classes, unambiguous and unique properties, datatypes, inverses, equivalencies, lists, and much more in DAML+OIL.

Note that Notation3 introduces a "context" construct, enabling one to group statements together and quantify over them using a specially designed logic vocabulary. Using this vocabulary, for example, one can express "or", using NANDs:-

{ { :Joe :loves :TheSimpsons } a log:Falsehood .
 { :Joe :is :Nuts } a log:Falsehood .
} a log:Falsehood .

Which can be read as "it is not true that Joe does not love The Simpsons and is not nuts". I resisted the temptation to make Joe a universally quantified variable.

Note that the above example does not serialize "properly" into XML RDF, because XML RDF does not have the context construct as denoted by the curly brackets in the example above. However a similar effect can be achieved using reification and containers.

The Power Of Semantic Web Languages

The main power of Semantic Web languages is that any one can create one, simply by publishing some RDF that describes a set of URIs, what they do, and how they should be used. We have already seen that RDF Schema and DAML are very powerful langauges for creating languages.

Because we use URIs for each of the terms in our languages, we can publish the languages easily without fear that they might get misinterpreted or stolen, and with the knowledge that anyone in the world that has a generic RDF processor can use them.

The Principle Of Least Power

The Semantic Web works on a principle of least power: the less rules, the better. This means that the Semantic Web is essentially very unconstraining in what it lets one say, and hence it follows that anyone can say anything about anything. When you look at what the Semantic Web is trying to do, it becomes very obvious why this level of power is necessary... if we started constraining people, they wouldn't be able to build a full range of applications, and the Semantic Web would therefore become useless to some people.

How Much Is Too Much?

However, it has been pointed out that this power will surely be too much... won't people be trying to process their shopping lists on an inference engine, and suddenly come up with a plan for world peace, or some strange and exciting new symphony?

The answer is (perhaps unfortunately!) no. Although the basic parts of the Semantic Web, RDF and the concepts behind it are very minimally constraining, applications that are built on top of the Semantic Web will be designed to perform specific tasks, and as such will be very well defined.

For example, take a simple server log program. One might want to record some server logs in RDF, and then build a program that can gather statistics from the logs that pertain to the site; how many visitors it had in a week, and so forth. That doesn't mean that it'll turn your floppy disc drive into a toaster or anything; it'll just process server logs. The power that you get from publishing your information in RDF is that once published in the public domain, it can be repurposed (used for other things) so much easier. Because RDF uses URIs, it is fully decentralized: you don't have to beg for some central authority to publish a language and all your data for you... you can do it yourself. It's Do It Yourself data management.

La Web Pedante

Unfortunately, there is an air of academia and corporatate thinking lingering in the Semantic Web community, which has lead to the term "Pedantic Web" being coined, and a lot of mis/disinformation and unecessary hype being disseminated. Note that this very document was devised to help clear up some common misconceptions that people may have about the Semantic Web.

For example, almost all beginners to RDF go through a sort of "identity crisis" phase, where they confuse people with their names, and documents with their titles. For example, it is common to see statements such as:-

 dc:creator "Bob" .

However, Bob is just a literal string, so how can a literal string write a document? What the author really means is:-

 dc:creator _:b .
_:b foaf:name "Bob" .

i.e., that example.org was created by someone whose name is "Bob". Tips like these are being slowly collected, and some of them are being displayed in the SWTips guide, a collection of Semantic Web hints and tips maintained as a collaborative development project.

Education And Outreach

The move away from the "Pedantic Web", to some extent, is all part of a movement to bring the power of the Semantic Web to the people. This is a well documented need:-

[...] the idea that the above URIs reveal a schema that somehow fully describes this language and that it is so simple (only two {count 'em 2} possible "statements"), yet looks like the recipe for flying to Mars is a bit daunting. Its very simplicity enables it to evaluate and report on just about anything - from document through language via guidelines! It is a fundamental tool for the Semantic Web in that it gives "power to the people" who can say anything about anything.

- EARL for dummies, William Loughborough, May 2001

RDF Schema and DAML+OIL are generally languages that need to be learned, however, so what is being done to accomodate people who have neither the time nor patience to read up on these things, and yet want to create Semantic Web applications? Thankfully, many Semantic Web applications will be lower end appliactions, so you'll no more need to have a knowledge of RDF than Amaya requires one to have a knowledge of (X)HTML.

Trust and Proof

The next step in the archtecture of the Semantic Web is trust and proof. Very little is written about this layer, which is a shame since it will become very important in the future.

In stark reality, the simplest way to put it is: if one person says that x is blue, and another says that x is not blue, doesn't the whole Semantic Web fall apart?

The answer is of course not, because a) applications on the Semantic Web at the moment generally depend upon context, and b) because applications in the future will generally contain proof checking mechanisms, and digital signatures.

Contexto

Las aplicationes en la Web Semantica dependera generalmente del contexto para permitir a la gente saber si deben o no dar cedibilidad a los datos. Yo yo obtengo un feed RDF de un amigo sobre las peliculas que ha visto, y como las ha valorado, yo se que valoro esa informacion. Ademas, puedo usar esa informacion y con seguridad dar credibilidad a esa informacion que el me ofrece, y entonces dejarla bajo mi juicio simplemente para cuanto yo acredito sus criticas de las peliculas que ha revisado.

Los grupos de gente tambien operan en un contexto compartido. Si un grupo esta desarrollando un servicio de depiction de la Web Semantica, catalogando quienes son las personas, cuales son sus nombres, y donde estan sus fotografias, entonces mi credibilidad sobre ese grupo dependera de cuanto acredito a las personas que elo estan desarrollando not to make spurious claims.

Asi el contexto es beneficioso ya que nos permite operar en escala local y media intiutivamente, sin tener que llegar a los complejos sistemeas de autentificacion y chequeo. De todas formas, que ocurre cuando conocemos el remitente, pero pero no podemos verificar que un cierto fragmento de datos RDF proviene de el? ahi es donde hacen su aparicion las firmas digitales.

Firmas Digitales

Las firmas digitales son simplemente pequenhos bits de codigo que uno puede usar para sin lugar a dudas verificar que alguien escribio cierto documento. Muchas personas son probablemente familiares con la tecnologia: es el mismo sistemas basado en llaves PGP-style thing that people use to encrypt and sign messages. We simply apply that technology to RDF.

Por ejemplo, digamos que tengo cierta informacion en RDF que contiene un enlace a una firma digital:-

this :signature  .
:Jane :loves :Mary .

To ascertain whether or not we trust that Jane really loves Mary, we can feed the RDF into a trust engine (an inference engine that has a little digital signature checker built into it), and get it to work out if we trust the source of the information.

Proof Languages

A proof language is simply a language that let's us prove whether or not a statement is true. An instance of a proof language will generally consist of a list of inference "items" that have been used to derive the information in question, and the trust information for each of those items that can then be checked.

For example, we may want to prove that Joe loves Mary. The way that we came across the information is that we found two documents on a trusted site, one of which said that ":Joe :loves :MJS", and another of which said that ":MJS daml:equivalentTo :Mary". We also got the checksums of the files in person from the maintainer of the site.

To check this information, we can list the checksums in a local file, and then set up some FOPL rules that say "if file 'a' contains the information Joe loves mary and has the checksum md5:0qrhf8q3hfh, then record SuccessA", "if file 'b' contains the information MJS is equivalent to Mary, and has the checksum md5:0892t925h, then record SuccessB", and "if SuccessA and SuccessB, then Joe loves Mary".

An example of this in Notation3 can be found in some of the author's proof example experiments, but here is the rules file:-

@prefix :  .
@prefix p:  .
@prefix log:  .
@prefix rdfs:  .

p:ProvenTruth rdfs:subClassOf log:Truth .

# Proof

{ {  p:checksum ;
          log:resolvesTo [ log:includes { :Joe :loves :MJS } ] }
log:implies
{ :Step1 a p:Success } } a log:Truth .

{ {  p:checksum ;
         log:resolvesTo [ log:includes { :MJS = :Mary } ] }
log:implies
{ :Step2 a p:Success } } a log:Truth .

{ { :Step1 a p:Success . :Step2 a p:Success }
log:implies
{ { :Joe :loves :Mary } a p:ProvenTruth } } a log:Truth .

The file speaks for itself, and when processed using CWM, does indeed work, producing the intended output. CWM doesn't have the capability to automatically check file checksums or digital signatures, but it is only a matter of time before a proper Semantic Web trust engine is written.

Ambient Information and SEM

The scope of information was discussed a little, but let's take into consideration what it really means to have a "local" and a "global" system.

In general, there are small and large scale systems, and interactions between the two will most likely form a huge part of the transactions that occur on the Semantic Web. Let's define what we mean by large, medium, and small scale systems.

Larga Escala

An example of a large scale system is two companies that are undergoing a merger needing to combine their databases. Another example would be search engines compiling results based upon a huge range of data. Large scale Semantic Web systems generally involve large databases, and heavy duty inference rules and processors are required to handle the databases.

Media Escala

Medium scale Semantic Web systems attempt to make sense out of the larger scale Semantic Web systems, or are examples of small scale Semantic Web systems joined together. An example of the former is a company trying to partially understand two large scale invoice formats enough to use them together. An example of the latter is of two address book language groups trying to create a super-address book language.

Pequenha escala

Small scale Semantic Web systems are less widely discussed. By small scale Semantic Web systems, we mean languages that will be used primarily offline, or piles of data that will only be transferred with a limited scope, perhaps between friends, departments, or even two companies.

Sharing data on a local level is a very powerful example of how the Semantic Web can be useful in a myriad of situations. In the next section on evolution we shall be finding out how interactions between the different sized systems will form a key part of the Semantic Web.

SEM - SEmantic Memory

The concept of a SEmantic Memory was first proposed by Seth Russell, who suggested that personal database dumps of RDF that one has collected from the "rest" of the Semantic Web (a kind of Semantic Cloud) would be imperative for maintaining a coherant view of data. For example, a SEM would most likely be partitioned into data which is inherent to the whole Semantic Web (i.e., the schemata for the major languages such as XML RDF, RDF Schema, DAML+OIL, and so on), local data which is important for any Semantic Web applications that may be running (e.g. information about the logic namespace for CWM, which is currently built in), and data that the person has personally been using, is publishing, or that has been otherwise entered into the root context of the SEM.

The internal structure of a SEM will most likely go well beyond the usual triples structure of RDF, perhaps as far as quads or even pents. The extra fields are for contexts (an StID), and perhaps sequences. In other words, they are ways of grouping information within the SEM, for easy maintainence and update. For example, it should become simple to just delete any triple that was added into a certain context by removing all triples with that particular StID.

A lot of work on the Semantic Web has concentrated on making data stores (i.e. SEMs) interoperable, which is good, but that has lead to less work being conducted on what actually happens within the SEM itself, which is not good, because the representation of quads and pents in RDF is therefore up in the air. Obviously, statements can be modelled as they would be for reification:-

rdf:Statement rdfs:subClassOf :Pent .
_:s1 rdf:type :Pent .
_:s1 rdf:subject :x .
_:s1 rdf:predicate :y .
_:s1 rdf:object :z .
_:s1 :context :p .
_:s1 :seq "0" .

But clearly a dedicated pentuples format is always going to be more efficient, and aviod the perils of reification:-

:x :y :z :p "0" .

This language also needs a default context flag that indicates the root context of the document. The root context of a document is the space to which the (non-quoted) assertions are parsed, the conceptual information space in which all of the assertions are taken to be true. Any quoted information in the document (for example, using the Notation3 context syntax) would be in a different (possibly anonymous) context than the root context of the document.

TimBL appears, gaguing from the CWM source code, to be using "...#_formula" as the root context for the document, which (if true) is a bit of a nasty hack... what if one creates a property with the same URI? Maintaining interoperability at this level of the Semantic Web is an important thing for the Semantic Web developers to be investigating at this stage.

Evolucion

A very important concept on the Semantic Web is that of evolution: going from one system into another. Two key parts of evolvability are partial understanding and transformability. We will find out next how these manifest themselves naturally when changing the scale of a system.

Partial Understanding: Large Scale to Medium Scale

The concept of partial understanding is a very important one on the Semantic Web, and can often be found in older documents that came out about the same time as the Semantic Web was first being theorized.

An example of partial understanding when moving a large scale system to a medium scale system is of a company trying to make sense out of two invoices, one from Company A and one from Company B. The knowledge that both of the companies use similar fields in their invoices is well known, so company trying to make sense out of the invoices can easily compile a master list of expenditures by simply scraping the data from the two invoice languages. Neither Company A nor Company B need to know that this is going on.

Indeed, TimBL included this example in his XML 2000 keynote:-

[...] what we'll end up doing in the future is converting things, so for example [...] in the Semantic Web we will have a relationship between two langauges so that if you get an invoice in a langauge you don't understand, and you have... some business software which can pay invoices... by following links across the Semantic Web, your machine will be able to automatically convert it from one language to another, and so process it.
- Tim Berners-Lee

Transformabilidad: de Pequenha Escala a Media Escala

An example of a small scale Semantic Web system joined together to make a medium sized Semantic Web system could be two groups that have published address book fomats wanting to make a larger and better address book format by merging the two current formats together. Anyone using one of the old address book formats could probably convert them into the new format, and hence there would be a greater sense of interoperability. That's generally what happens when one goes from a small scale Semantic Web system into a medium scale Semantic Web system, although this is often not without some disadvantages and incompatabilites. The Semantic Web takes the sting out of it by automating 99% of the process (it can convert field A into field B, but it can't fill in any new data for you... of course, new fields can always be left empty for a while).

Facilitando Evolvability

How do we document the evolution of languages? This is a very important and indeed urgent question, and one which TimBL summarized quite neatly:-

Where for example a library of congress schema talks of an "author", and a British Library talks of a "creator", a small bit of RDF would be able to say that for any person x and any resource y, if x is the (LoC) author of y, then x is the (BL) creator of y. This is the sort of rule which solves the evolvability problems. Where would a processor find it? [...]

- Semantic Web roadmap, Tim Berners-Lee

Una posible respuesta es: bases de datos de tercera parte. Muy a menudo, it is not practical to have (in TimBL's example) either the LoC or or BL record the fact that two of their fields are the same, so this information will have to be recorded by a reputable third party.

One such "third party" that was set up to investigate this is SWAG, the Semantic Web Agreement Group. Co-founded by Seth Russell, Sean B. Palmer, Aaron Swartz, and William Loughborough, the group aims to ensure interoperability on the Semantic Web. They set up what is possibly the first ever third party Semantic Web dictionary, the WebNS SWAG Dictionary.

Intertwingling: Difficult, But Important

Although the Semantic Web as a whole is still very much at a grassroots kind of level, people are starting to take notice; they're starting to publish information using RDF, and thereby making it fit for the Semantic Web.

However, not enough is being done to link information together... in other words, the "Semantic" part of the "Semantic Web" is coming along nicely, but where's the "Web"? People are not using other people's terms effectively; when they use other terms, they often do so because they're aimlessly trying to help, but just generating noice in the process. If you're going to use other people's data, try to find out what the advantage is in doing that beforehand. For example, just because you use the term "dc:title" in your RDF rather than a home brewed ":title", does that mean that suddenly a Dublin Core application is going to be able to "understand" your code? Of course not. What it does mean however is that if the "dc:title" property in your instance is being put to use in such a way that information may be need to repurposed from it in the near future, then you may gain some advantage because "dc:title" is such a commonly used term, you may be able to modify a current rules file, or whatever.

Otra parte del problema may be due to a problem similar to the one that the early World Wide Web experienced: why bother publishing a Web site when there is no one else's site to link to or be linked to? Why bother publishing a Web site when so few people have browsers? Why bother writing a browser when there are so few Web sites? Some people have to make the leaps for it all to happen, and that's a slow process.

What can be done about the situation? Well, it may hopefully sort itself out. Another well-known principle that applies very well to Semantic Web applications is that there is no point in reinventing the wheel; viz., if someone has already invented a schema which contains a comprehensive and well understood and used set of terms that you also need to use in your application, then there is no point in trying to redo the work that they have done. At some points this may lead to a form of "schema war", but survival of the fittest should see to it that a core of the best schemata are put to the most use. This is probably what TimBL means when he says that terms will just "emerge" out of the Semantic Cloud, that when people keep using the term "zip", rather than just recording that my term "zip" is equivalent to your term "zip" which is equivalent to someone else's term "zip", we'll all just use the same URI, and hence interoperability will be vastly improved.

Does It Work? What Semantic Web Applications Are There?

I addressed this in a previous article: The Semantic Web: Taking Form, but it does bear repeating: the Semantic Web already works, and people are using it.

Aplicaciones de la Web Semantica

Unfortunately, the Semantic Web is dissimilar in many ways from the World Wide Web, including that you can't just point people to a Web site for them to realise how it's working, and what it is. However, there have been a number of small scale Semantic Web applications written up. One of the best ones is Dan Connolly's Arcs and Nodes diagrams experiment:-

One of the objectives of the advanced development component of the Semantic Web activity is to demonstrate how RDF and Semantic Web technologies can be applied to the W3C Process to increase efficiency, reliability, etc. In the early stages of developing an RDF model of the W3C process, the tools I was using to visualize the model while working on it started working well enough that I started applying them to all sorts of stuff.

Desde luego, este es quiza un proyecto de la Web Semantica orientado hacia la demostracion, pero ilustra la feasibility de las aplicaciones facilmente construidas usando herramientas de la Web Semantica.

Otro buen ejemplo de la Web Semantica como herramienta de trabajo es la pagina RDFWeb. RDFWeb is a RDF database driven hypermedia blogspace, a site where all information is stored as RDF, and then that RDF used to render XHTML. Plans are underway to incorporate more advanced Semantic Web principles into the site.

Que Puedo Hacer Para Ayudar?

Hay muchas formas en las que cualquiera puede contribuir extendiendo la Web Semantica. Aqui estan algunas de ellas:-

  • Publicar datos utiles para todo el mundo en RDF.
  • Escribir un motor de inferencias en el lenguaje que elijas.
  • Corre la voz: ensenha a los demas e indaga.
  • Colabora en el desarrolo de RDF Schema y/o DAML.
  • Contribuye in representing state in RDF, a rather neglected field of research.
  • Aplica tus conocimientos de desarrollo a la Web Semantica, danos una nueva perspectiva sobre la que abordarla.
  • En lugar de usar algun sistema propietario para tu proximo programa, considera hacer un proyecto basado en la We Semantica.

There are many other ways in which one can help as well: ask in the community for more details.

Enlaces relacionados

As of 2001-09, the amount of Semantic Web Education and Outreach materials can only really be described as "pitiful" (hence this introduction, for a start). Here's a short list of some of the buenos primers and materials currently available, in no particular order:-

Para mas informacion, y todas las ultimas noticias, etc., la Guia de Recursos para el Marco de Descripcion de Recursos (RDF) de Dave Beckett es absolutamente brillante.

Muchos desarrollares de la Web Semantica y RDF frecuentan la sala de chat RDF IG IRC, en irc.openprojects.net, #rdfig.

Agradecimientos

Este texto fue elaborado originalmente por Sean B. Palmer en septiembre del 2001. Adaptado y traducido posteriormente por Ramon Antonio Parada.

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