smart homes – house assistive technology

Posted on January 19, 2012 by admin

smart home
Smart homes controlled by a central computer is not just a phantasy story. Assistive house technology is a fact and offers many potentials. There are allready computer based systems that can control many functions of the house. So the time of the future house has arrived. The most common house system is the lights and appliances program, that usually includes computer-controlled switching equipment. This program provides control of lights and appliances anywhere in the house. It is even possible to be done without any special house wiring . The user controls the lights and turns appliances on and off from a bank of switches displayed on the screen. The is the potential to use that even by distance through internet. That means that you can be on holidays and control and watch your house. One more plus is that This will look really impressive especially if you combine it with a nice futuristic interior design and decoration. Free tips for futuristic home decoration can be found at Free interior decorating ideas. So get ready for the future house!

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What do I need to watch 3D movie at home?

Posted on December 3, 2011 by admin

First of all you need a 3D TV. But this is not enough. Some people think that by buying a 3D TV they can see 3D films even by their DVD player using 3$ glasses from ebay. It is also nessecary a 3D blue ray player. DVD players, even simple Blue ray players can not play good quality 3d movies. Some people ask: Can I see 3d movies through my playstation 3? The answer is yes, you can also see 3d movies through the media player of playstation 3 if your firmware is not old and your hdmi cable is not less than 1.3. One more thing you will need is active 3d glasses. The 3$ glasses do have a difference comparing to the 80$ 3D glasses. With simple 3d glasses you can see old type 3D movies, like the ones at the 70′s. Not enough to impress the girl you invited to see 3d Movie together. Prices at 3d equipment are falling very fast, they allready cost half price than last year.

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Games and web semantic

Posted on April 27, 2011 by admin

One of the most popular internet subjects is games. Games have allways been a main function even for the first PCs. How will the semantic web affect the video games? How can the new technology be used?

Storing data in RDF

Games can store many kind of information in RDF. Let’s see an example for world of Warcraft character

<rdf:RDF xmlns:rdf=”http://www.w3.org/1999/02/22-rdf-syntax-ns#”

xmlns:wow=”http://www.worldofwarcraft.com/ns/wow#”>

<rdf:Description rdf:ID=”charactername”>

<wow:Name>charactername</wow:Name>

<wow:Armor>150</wow:Armor>

<wow:Strength>25</wow:Strength>

</rdf:Description>

</rdf:RDF>

someone can give a lot of information to the RDF about the world of the game or the servers.

Do flash games sites change?

Last years are created games that do not require any installation. That kind of games are the browser games and flash games. Flash games sites do not seem to be affected by the semantic web technology. At least at the game function. Things are simple there. It is more flash programming and not web programming. Let’s see a sample of a new generation flash game site. flash games. We chose a Greek flash game site ,to avoid doing an advertisemt. The basic gaming functions are same. Game reviews and information sites are affected as any web 3 magazine. Let’s see a German site example about system requirements for pc games. Systemvoraussetzungen.

When web 3 is more established, I believe games will be affected even more as it is the second most popular thing , people search at internet.


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Semantic Web Glossary

Posted on April 20, 2011 by admin

When I was learning all these terms one by one, I really would have benefited from a central and comprehensive place where I could have gone to look up terms. I put the glossary together, hoping to make it as comprehensive as possible and will be adding to it and improving it moving forward. I hope it helps people.

ABox - Used to describe statements in ontologies; an assertion; a fact that is associated with a terminological vocabulary within a knowledge base; A-Box statements are sometimes associated with instances of T-Box classes.

Blank Node – A resource, or node in an RDF graph, which is not identified by a URI; can be used as subject or object in an RDF triple (RDF statement).

Closed World Assumption – Presumption stating that the statements we have are the only statements that need be considered. If something is not referenced in our data set, we assume it does not exist.

DAML+OIL - A successor language to DAML and OIL that combines features of both; it is now “outdated” because it was superseded by Web Ontology Language (OWL).

DataTypeProperty - Relationship between instance of classes and literal values such as string, number, and date.

Description Logics (DL) – A family of knowledge representation languages which can be used to represent the concept definitions of an application domain in a structured and formally well-understood way. See also OWL Lite, OWL DL and OWL Full.

DL – See Description Logics.

Entailment (logical implication) – In Semantic Web, one of the key inference ideas; a relationship between two pieces of knowledge where the truth of the first piece of knowledge requires the truth of the other.

Ground RDF Graph - RDF graph with no blank nodes.

HTML – Hypertext Markup Language; language used to encode formatting, links and other features on Web pages.

Individuals – Instances of classes; properties may be used to relate individuals to each other.

Inference – Process of deriving a conclusion from premises; in semantic web it is performed by a reasoner software and is used to extract explicit knowledge from implicit logic and add it to the original data set.

Literal – Used to identify values such as numbers and dates by means of a lexical representation. A literal may be the object of an RDF statement, but not the subject or the predicate.

Model Theory – specifies the semantics of a formal language; assumes that the language refers to a ‘world’, and describes the minimal conditions that a world must satisfy in order to assign an appropriate meaning for every expression in the language.

N-Triple – Also N-Triple format; a line-based, plain text format for encoding an RDF graph that is intended for better human readability of the RDF document.

Natural Language Processing (NLP) - Field of computer science concerned with the interactions between computers and human (natural) languages. Natural language generation systems convert information from computer databases into readable human language while natural language understanding systems convert samples of human language into more formal representations that are easier for computer programs to manipulate.

Object – In an RDF triple, the subject is the third of the three [Subject Predicate Object]; it is either a resource (blank node is a resource also) or a literal.

ObjectTypeProperty - Relation between instances of two classes.

Ontology – A data set describing things and their existence in the world.

OWL - see Web Ontology Language.

Open World Assumption – presumption stating that everything we don’t know is undefined.

OWL Lite - An owl class (owl:class) is defined as subclass of rdfs class (rdfs:class); not all classes of RDF document can be an instances or subclasses of an owl class (owl:class); as a result, a valid rdf document cannot be considered as a valid OWL Lite or DL document. It is different from OWL DL in lower level language details and constraints.

OWL DL – An owl class (owl:class) is defined as subclass of rdfs class (rdfs:class); not all classes of RDF document can be an instances or subclasses of an owl class (owl:class); as a result, a valid rdf document cannot be considered as a valid OWL Lite or DL document. It is different from OWL Lite in lower level language details and constraints.

OWL Full - A class (owl:class) is defined as equivalent to an rdfs class (rdfs:class). This enables any valid rdf document to be considered as a valid OWL full document. Similarly, In OWL full, owl:ObjectTypeProperty is considered equivalent to rdf property. DataTypeProperty, which is a subclass of rdf:property, is also a subclass of owl:ObjectTypeProperty. This means that any property in OWL that is defined as datatype can also be interpreted as objectype property. This allows much of the expressiveness in OWL full.

Pellet - Open-source Java OWL DL reasoner.

Predicate – In an RDF triple, the subject is the second of the three [Subject Predicate Object]; it is always a property.

Property – A binary relation that states relationships between classes/individuals or from an class/individual to data value. Property can be further distinguished as ObjectTypeProperty or DataTypeProperty.

RDF – Resource Description Framework. An XML-based language for describing online resources.

RDF Graph - Set of RDF triples.

RDF Subgraph – A subset of the triples in the graph.

RDF Triple – see Triple.

RDFS – Resource Description Framework Schema.

Reasoner – Software able to infer logical consequences from a set of asserted facts or axioms which creates a richer knowledge base.

Resource – Anything that has a valid unique resource identifier (URI).

Semantic Web – Extension of the World Wide Web in which the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content; also known as web3.0

SHER - Highly scalable Pellet-backed OWL DL reasoner.

SPARQL – SPARQL Protocol and RDF Query Language (pronounced “sparkle”) is an RDF query language much like SQL is a relational DB query language.

Statement - an assertion about the world; in semantic web it is usually a part of a vocabulary or an ontology; it usually consists of a “triple” structure of [subject predicate object].

Subject - In an RDF triple, the subject is the first of the three [Subject Predicate Object]; Object – In an RDF triple, the subject is the third of the three [Subject Predicate Object]; it is always a resource (blank node is a resource also).

T-Box – used to describe statements in ontologies; T-Box statements describe a system in terms of controlled vocabularies, for example, a set of classes and properties. T-box statements are sometimes associated with object-oriented classes.

(Sir) Timothy John Berners-Lee – an English computer scientist and MIT professor credited with inventing the World Wide Web and semantic web.

Triple – A basic RDF statement resembling the English-Language construct of [subject predicate object] that is made up of [Resource property Resource] or [Resource property Literal].

Typed Literal - A string combined with a datatype URI in order to express information about the datatype of the literal i.e. weight, length, height.

URL (Uniform Resource Locator) – The familiar constructs such as http://www.semanticalley.com/ that are used in hyperlinks.

URI (Universal Resource Identifier) – URLs are the most familiar type of URI; a URI defines or specifies an entity, without necessarily by naming its location on the Web.

Vocabulary (of a graph) – Set of classes and properties which occur as the subject, predicate or object of any triple in an RDF graph.

W3C – World Wide Web Consortium.

Web 1.0 – Static, minimally-interactive pages containing photos and text documents.

Web 2.0 – Use and design of the web with strong emphasis on reusability and sharing, with information traveling fast and being easy to get to. Widgets and tagging are two examples of features in Web2.0

Web 3.0 - see “semantic web.”

Web Ontology Language (OWL) – Family of knowledge representation languages for authoring ontologies, consisting of three languages: OWL Lite, OWL DL, and OWL Full.

XML – eXtensible Markup Language; general-purpose specification for creating custom markup languages.

Posted in Semantic web | Tagged | 2 Comments

Web 3 changes

Posted on April 20, 2011 by admin

Semantic Web and Web 3 are very close related. For many people they are considered to be allmost synonymous. Web 3 will be more graphic enviroment and less browser applications. Also it will be more focus on mobile phones and non-computer based devices, geographic based information retrieval” and even more applicable use and more Artificial Intelligent.Web 3 has started getting in our lifes. Let’s see a table with some basic changes comparing to web 2 and web 1

Web 1.0 Web 2.0 Web 3.0
read-only content and static HTML websites user-generated content and the read-write web The portable personal web
Focused on companies Focused on communities Focused on the individuals
Static pages Blogs Lifestream
Owning content Sharing content dynamic content
HTML, portals PHP, XML,  RSS Semantic web
Web forms Web applications Widgets
Directories Tags User behavior
Netscape Google iGoogle
Pages views Cost per click User engagement
Advertising Media Advertainment

Web 3.0  will be about semantic web , personalization (e.g. iGoogle), intelligent search and behavioral advertising. Anyway the pass from web 2 to web 3  still needs a lot of time

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The plus of semantic web languages

Posted on April 20, 2011 by admin

The plus of Semantic Web languages, is the fact that anyone can create one. How can someone do that? Just by publishing some RDF that describes a set of URIs, what they do, and how they are used.  (URI = Uniform Resource Identifier.  A Web identifier,  like strings starting with http: or ftp:  for example. Anyone can create one, and the ownership of them is delegated)

Two of the most powerful languages for languages creation, are RDF Schema and DAML. As someone uses URIs for each of the terms in our languages,  can publish the languages easily without fear that they might get stolen, and knowing that anyone  that has a generic RDF processor can use them.

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What is the semantic web?

Posted on April 19, 2011 by admin

Semantic’s root is the Greek word “Semanticos” which means significant. The Semantic Web is the web of data, that enables machines to understand the meaning and the information on any internet site in the world . It extends the  human-readable web pages, by inserting machine-readable metadata with information about the  pages and the way they are related to each other. That helps  agents to access the Web more easy and intelligent way, and perform tasks on behalf of users.

In many ways, the Semantic Web translates human and computer languages  into something common in order to perform complex negotiations . This promotes standards for databases and creates artificial intelligence to bear decryption between similar concepts.

The term “Semantic Web” is often reffered to the formats and technologies that enable it. like  the Resource Description Framework (RDF),  interchange formats data (e.g. RDF/XML, N3, Turtle, etc), and notations such as RDF Schema (RDFS) and the Web Ontology Language (OWL).  All of these provide a formal description of concepts, terms, and relationships within a web domain.

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Drupal: The Semantic Web Enabler

Posted on February 27, 2009 by admin
Benjamin Melancon and Stephane Corlosquet recently gave a talk at a New York Semantic Web Meetup, organized by Marco Neumann, about how the Content Management System (CMS) Drupal is using Semantic Web, and much more importantly about how Drupal is actually helping make Semantic Web a critical mass reality..

Since the key questions here are “what is Drupal? What do they have to do with Semantic Web? Why particularly Drupal, and not some other technology is important? And finally, how they do they what they do?”

As I already mentioned, Drupal is a Content Management System. It lets people create relatively simple HTML pages without actually having to code the HTML by hand. This is really good in non-semantic systems, but it severely limits the growth of Semantic Web pages because it only creates the HTML and does not offer an RDF solution. Although Drupal had vague plans to enable RDF solutions for their sites as early as 2000, but after a “Semantic Web dark age” they have only recently began to implement RDF solutions. But they have made great strides.

The reason it is very important for CMS to enable Semantic Web is to remove the burden on people to have to encode the RDF by hand. RDF is meant for machines. It is NOT user friendly to human eyes and is syntactically cryptic. Additionally, due to its cryptic nature, is quite error-prone to write by hand. While there are software tools like JENA that help write out the RDF, people still have to construct it. Because making an RDF website requires such a “Herculian” effort, it is actually quite a barrier to critical mass adaptability of Semantic Web. Once people can simply say what they want on their page and have the option to export that page entirely in RDF, a significant step to critical mass adoption of Semantic Web will take place.

Since Drupal enables website creation, it is natural for it to to lead the Web content producers into the Web3.0 age. In fact, to more firmly ask answer the question of what Drupal has to do with Semantic Web, it is Drupal’s responsibility to help enable it. And if I want to be very dramatic, and why not take such an opportunity, then right here and now I will raise my flag and proclaim that as the conduit through which content is created, “knowledge, Internet, and with it world progress depends on Drupal taking the step forward towards enabling Semantic Web!”
(Was that too dramatic?)

Now I will very briefly go over how they actually do what they do. By default, Drupal still treats new content as though it is Web2.0 content and allows users to create their pages as they always have because after all, Semantic Web is just an addition on top of the current Web. Once some content is put together though, a user can export it in RDF, using any vocabulary or ontology they want, which enables the entire page to potentially be shared across the Web.

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FUN RDF: A Simple Introduction

Posted on February 16, 2009 by admin

Recently, Marco Neumann asked to write a “fun introduction to RDF” article. Since not long ago I was beginning to learn it myself, and having the learning struggles fresh in my mind, I thought it would help many people. I happily agreed, but to myself I thought “you want me to do what? How is that even possible to make this dry topic fun?” But here I am wondering how Shakespeare, Poe and Kierkegaard would “pen” such things…

To introduce the subject, the Resource Description Framework (RDF) is a language for representing information. Try an acronym to better remember it: Really Digital Fun; or you know, you can always try to remember the actual terms the abbreviation stands for like Resource Description Framework. Done, that is it. Lesson over, go home. Just in case you are still reading I will explain a bit more.

RDF represents information by describing “resources” and literal values. It treats everything connected to a URI (more on that a bit later) as a resource and offers a way to logically connect the resources. It is a breakthrough in Web technology. Let me explain how we arrived here. Since the mid 1990’s the Internet world has been familiar with HTML having tags that can fully describe a Web page. In the late 1990’s we learned about XML, which is flexible and can describe anything (my grandmother, the news, Chelsea Football Club, China or various business entities) we want. The problem with XML was that we could only share it with a limited set of companies and people who knew about the tags the owner created. RDF adds a common XML-based syntax. Now machines can be made to “know” the tags that describe the documents we make, which allows near infinite sharing between machines and ultimately users everywhere. Let’s stop for a second and consider what that means. You thought I was going to explain the implications to you? Nooot! But it is a creative space, so it might be fun to think about it.

RDF is tailored for situations in where information needs to be processed by software applications rather than being only displayed to people. Because it provides a common framework for expressing information, this information can be exchanged and used by applications without loss of meaning. This allows information to be made available to applications other than just those for which it was originally created, increasing the potential use of RDF-based applications by making the original ontology available for anyone to easily adopt and use.

Let’s take a moment and focus on why a data set in Semantic Web is not called a “data set,” but (very gloriously) an ontology. The “Open World” nature of RDF suggests that everything we don’t know is undefined which gives rise to the need to have comprehensive data collections. But a comprehensive data collection is by nature an ontology because it attempts to cover an entire domain of a subject. Since we construct our own ontologies (and reuse others’ ontologies) in Semantic Web, the makers of ontologies create reality!

For example, if I am describing a resource “elephant” and I want him to be able to fly, in my ontology I can do just that. Once I do that, in the world of my ontology it is true that elephants can fly. Elephants fly for whoever reuses my ontology and since RDF allows increased reuse of data this can have significant consequences. The ontology-maker creates a “vocabulary” and a reality that the ontology users must accept. In creating pseudo realities we are combining Computer Science and Philosophy. That is nice nerdy fun, right?

It is interesting to point out that although people have attempted to create and use common ontologies ever since the Greek philosophers introduced the concept, RDF makes these ontologies “machine-readable” and thus introduces unprecedented ability to share the knowledge. In the past, ontologies were endemic to a culture and a physical location because knowledge could not spread due to physical constraints, but with RDF and machine-readable ontologies comes the potential to make really global ontologies if one is cyc enough to try such a thing.

It is easy to understand how RDF works internally. RDF statements are organized into triples, each of which resembles a simple English sentence: [subject predicate object]. An RDF triple is more like: [Resource property Resource] or [Resource property "LiteralValue"]. Resources and properties are uniquely identified by a URI (Uniform Resource Identifiers). An example of representing myself would be:

Resource: http://www.semanticalley.com/onto/2009/contact#AlexGenadinik

I also want to say that I am a person:

Resource: http://www.semanticalley.com/onto/2009/contact#Person

Now I want to make a possible “country” property for myself:

Predicate: http://www.semanticalley.com/onto/2009/contact#countryOfResidence

RDF allows to describe resources like “country” with Literal values such as “United States” for example.

RDF also uses values from other literal datat ypes such as integers and dates, as possible values of properties. This makes it very easy to express that AlexGenadinik’s country of residence is UnitedStates. In RDF it would just be the statements we created above. I will put them here again for convenience:

http://www.semanticalley.com/onto/2009/contact#AlexGenadinik
http://www.semanticalley.com/onto/2009/contact#countryOfResidence
http://www.semanticalley.com/onto/2009/contact#”United States”

Because having the above three lines to express a simple statement is cumbersome for human eyes, RDF composers use shorthand notation. For example, you can also say that AlexGenadinik is a Person with the following “triple” (using shorthand notation): myOntology:AlexGenadinik rdf:type myOntology:Person where myOntology and rdf are shorthand abbreviations for long URI’s.

To offer a slight recap, two things are needed to be able to make such statements:
1) A system of machine-processable identifiers for identifying a subject, predicate, or object in a statement without any possibility of confusion with a similar-looking identifier that might be used by someone else on the Web.
2) A machine-processable language for representing these statements and exchanging them between machines.

The Web already provides one form of identifier, the Uniform Resource Locator (URL) which is used to locate pages on the Web. For simply identifying things without needing to locate them, the Web provides a more general form of identifier, called the Uniform Resource Identifier (URI). In my RDF statements it was the following: http://www.semanticalley.com/onto/2009/contact

URI’s can be created to identify anything that needs to be referred to in a statement, including real electronic documents and images that are found under URLs. In addition, URIs can also be used to describe things like human beings, corporations, and books, and last but not least abstract concepts that may or may not physically exist, such as the concept of a “sky” whatever it might be. It is important to remember that anything that is identifiable by a URI reference is a resource. A browser may not be able to find anything under that address, but that is ok because we only need the URI to uniquely identify something.

Note: When making URI’s it is good practice to use domains which you can control, like www.semanticalley.com in my case because I own that domain name. If I used someone else’s domain and that person made an identical URL/URI it would potentially cause confusion and possibly errors.

Once a collection of RDF triples (same as RDF statements) is put together, it forms a “graph” of the collection of statements, representing their relationship to each other. In the next “FUN RDF” blog post I will write about a few slightly more advanced issues of RDF and RDF graphs.

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Smart Way to Compress Graph Data (or what I really wanted to call this blog post: Reasoning at IBM: A First)

Posted on February 6, 2009 by admin

At a recent New York Semantic Web meetup organized by Marco Neumann at NYU, Achille Fokoue, a researcher at IBM in the Thomas J. Watson Research Center in Hawthorne, New York, gave a talk on a highly expressive reasoner technology under development at IBM.

So far I have not had a blog post describing reasoners in detail, so before proceeding to talk about this specific reasoner from IBM, I will explain what a reasoner is.  It is software that takes existing data (in a certain widely accepted format called RDF syntax, which enables the reasoner to understand the logical connection of the discrete pieces of data) and logically connect the bits of data to see if, when taken as a whole, there can be more logically inferred knowledge (not already explicitly stated within the knowledge base) according to the existing logic of the system.  The simplest classical example is that if you have knowledge that A –> B and B –> C, the reasoner can “realize” and “infer” that A –> C, thus adding more explicit knowledge to the original knowledge base, making it richer.

The particular reasoner SHER, created at IBM is highly expressive and scalable OWL DL reasoner.  IBM started the project four years ago during the time of the emergence of OWL.  This new ontology language brought with it quite a bit of excitement about using ontologies to represent data.  Unfortunately it was not without its problems.  Adding extra expressions in a description language (DL) adds to the complexity of the reasoning, and it is particularly difficult to ensure logical consistency of big ontologies.  These two problems were IBM’s motivation for beginning the SHER project.

The purpose of the SHER reasoner is to reason over very large ontologies and the key to its magic is that it is made to actually not reason over an entire set of data.  Instead, it tries to understand the summary of the given knowledge base.  If the summary is consistent, then SHER knows that the T-Box was consistent.  Before I go on, let me explain what happens if the summary is deemed inconsistent.  The reasoner does something called “refinement” where it decomposes the part of the summary that is responsible for the inconsistency and changes the original ontology by creating more granular nodes and constantly splitting apart the problem areas to change them, making them consistent.  Then SHER again checks that the new data’s summary is consistent and repeats this process of refinement until the entire summary is consistent.  Once that is achieved, SHER reasons over the summary at query time.

Ultimately the SHER reasoner is able to cut down reasoning by many orders of magnitude.  What used to take days or weeks to now takes a mere twenty minutes.  This is quite a significant feat in the world of semantic web because it enables reasoning over very large data sets realistic, whereas before the available reasoners were only effective over small, “toy” (according to some) data models.  SHER is a great tool and in the right hands it will enable amazing achievements.  Now, only if it was freeÖcommon IBM!?

For more information about the SHER reasoner and the presentation, contact:

Achille Fokoue

http://domino.research.ibm.com/comm/research_people.nsf/pages/achille.index.html

Software Research Group

IBM Thomas J. Watson Research Center

Hawthorne, New York

The slides for the presentation are available here:

http://www.swnyc.org/ftp/SHERAndItsApplications.ppt

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