Semantic Web

Overview
The Semantic web (often referred to as Web 3.0 ) is a concept, first named by Tim Berners-Lee, for a "web of knowledge" in which world wide web documents' contents would be annotated and classified so that computers can parse the classifications and provide search results based on the semantic information (what the content means), rather than simply on matching of text strings. There is also a W3C standards effort related to this concept. Semantic web was developed to meet a specific deficiency in web based communications. Although well defined in RFC's, HTTP is architected to perform exchange of information that is delimited and optimized for presentation. That is, the use of HTML is designed to communicate the appearance of documents within web browsers. This is wonderful when attempting to create a document that will render in the same form across multiple platforms (or web browsers) but is problematic for transmitting meaning of data. There are a few HTML specifications (notably META tags and other document head elements ) that convey meaning, but these are precious few.

In order to associate meaning with content, Semantic Web utilizes structures for categorization. While a web page about soccer might specify how pictures and text should be arranged, what colors and font to use, and other presentation data, a similar Semantic Web document would convey the fact that the data pertained to the sport of soccer, perhaps a list of teams, scores of recent matches, and other data in categorization containers. This presentation allows other consumers (mainly programs) of the data to parse and utilize the data in meaningful ways. As opposed to modern web crawlers which must catalogue, index, and apply a certain amount of artificial intelligence to derive the meaning of documents on the web, semantic web allows data to be parsed easily for meaning - ultimately resulting in greater ability to share information.

One interesting challenge that faces semantic web is the ability to not only transmit data, but also to associate metadata. Metadata is descriptive information that conveys relationships between data types. In order to provide a flexible framework that is capable of transmitting multiple different types of data, as well as the meaning and relationships of that data, semantic web has integrated metadata into the format. This allows dynamic and unpredictable data formats and types to be transmitted and consumed by facilitating consumers' ability to process data by utilizing the embedded metadata to parse and understand data and inter-relationships.

What differentiates the Semantic Web from existing data structures is the use of URIs to uniquely identify things, and relationships between things. The sort of problem scenario that Semantic Web technologies try to solve are those involving multiple disparate source of data - for instance, hooking together train timetables and class timetables, so a student can automatically plan their travel itinerary without having to manually match the data together.

Semantic web is closely tied to microformats with are an alternative way to embed meaning into HTML documents. Microformats use standard HTML tags along with generally agreed upon conventions for attributes, in order to delineate certain data within documents. For instance, microformats can be used to embed contact data or calendar data in web pages for easy integration with other programs. This can allow users of popular calendaring or contact management software to simply click on elements within web pages and import calendar events, or contacts, directly into their calendaring or address book software.

The W3C have put forward a variety of standards built on top of the Resource Description Framework, a formal semantic model for representing things and the relationships between them.

Triplestore
Semantic web makes use of the triplestore data convention in order to relate objects and meaning. Triplestore is a rather simple linguistic convention that makes it easy to classify data and make connections. Triplestore takes the form "Subject" - "Predicate" - "Object". For example:

Garden location Backyard Firstrow location Garden Firstrow plantedWith Beets Firstrow plantedWith Carrots

Using this standard convention it is easy to catalogue data and to trace relationships between them. For instance, using the above example I can figure out what is planted in the first row of the garden in the backyard by tracing the relationships:

?Garden location Backyard -> finds the Garden I'm looking for ?Firstrow location Garden -> finds the row in the Garden just retrieved Firstrow plantedwith ?Veggie -> gets the vegetable planted in the first row

This rather simple model makes it possible to define (and query) complex relationships without first having a defined data model. This convention gives semantic web the adaptability to handle evolving dynamic data without constraining that data. This also means that the model doesn't have to be redefined to deal with emerging data types.

Triplestores can be used to create complex graphs of data. When expressing these data using RDF/XML they are typically rendered as N-Triples, which are expressed in plain text and used for transmitting this data across the network. N-triples do contain redundancy, however, so when moving N-triples across the wire it is common to utilize the RDF N3 notation, which compresses the data by removing duplication.

RDFa
Although using RDF is compact, it is not easily human readable. RDFa is a response to the disparity of data presentations between XHTML and RDF. RDFa allows RDF data to be embedded in XHTML content. Using standard XHTML tags like the &lt;span&gt; tag semantic web data can be mixed into XHTML presentation. For example:

&lt;span xmlns:example="http://example.tld/example/0.a" about="http://foo.tld/bar.rd#ts" property="example:bar" content="some_data"&gt;Some XHTML for presentation&lt;/span&gt;

Programming with Semantic Web
Because RDF is an open format, libraries exist for almost every programming language to make it easy for programmers to produce and consume RDF data. Some examples include the RDF.rb library for Ruby, JRDF for Java, a PEAR RDF package for PHP and many more.

Medicine
Semantic models seem the major trend in expert support to medicine. As an example of how semantic methodologies are used, consider several isolated concepts, which could be considered "nouns":
 * beta-adrenergic antagonists (i.e., beta blockers)
 * bradycardia (i.e., slow pulse)
 * asthma
 * hypertension
 * benign hand tremor

One of the notations for relationships is the Unified Medical Language System® (UMLS®). Informally, some of the "verb" semantic relationships among the above could be:
 * beta-adrenergic antagonists TREAT hypertension and benign hand tremor
 * beta-adrenergic antagonists CAUSE bradycardia
 * beta-adrenergic antagonists TRIGGER asthma

"Hypertension" would have a number of other TREATS relations, from drug classes such as thiazide diuretics, angiotensin-II converting enzyme antagonists, calcium channel blockers, angiotensin-II receptor blockers, etc.

ULMS is now being extended with formal ontologies:

Semantic Web in CMS
Content management systems (CMS) can benefit greatly from RDF features. RDF is an expressive means by which CMS can both publish and consume data. Because RDF makes data more easily machine readable it is perfect for systems that integrate data (such as CMS).

Drupal
The Drupal content management system is making a big push to include RDF and semantic web as part of the upcoming Drupal 7 release. There is a Drupal group devoted to semantic web as well as a code sprint devoted to the topic. With over significant and growing market share of CMS, Drupal's support of semantic web will mean a vast increase in implementation of RDF.

Wordpress
Wordpress has several third party plugins that implement RDF.

MediaWiki
MediaWiki has Semantic MediaWiki to integrate the Semantic Web in a wiki setting.

Other notable uses
Facebook recently announced support for open graph protocol which is an RDF implementation of semantic web.