The Semantic Web

Related Subjects:

How did the Semantic Web begin ?

As most things do, the Semantic Web started small. An article in the May 2001 issue of Scientific American described a futuristic world where software agents automatically schedule an entire series of medical treatments via the Semantic Web.

The article states that:

The Semantic Web will bring structure to the meaningful content of Web pages, creating an environment where software agents roaming from page to page can readily carry out sophisticated tasks for users

Software agents have been a hot topic for about the last 10 years. As a simple definition, they are discrete pieces of software that do useful things in flexible ways. There are several and commercial variations of an Agent Standard. Agents will often use rules and other powerful conceptual structures to implement complex tasks.

The Scientific American article continues:

The real power of the Semantic Web will be realized when people create many programs that collect Web content from diverse sources, process the information and exchange the results with other programs. The effectiveness of such software agents will increase exponentially as more machine-readable Web content and automated services (including other agents) become available. The Semantic Web promotes this synergy: even agents that were not expressly designed to work together can transfer data among themselves when the data come with semantics


An Aside on Software Agents

The Wikipedia defines a software agent as: "... an abstraction, a logical model that describes software that acts for a user or other program in a relationship of agency[1]. Such "action on behalf of" implies the authority to decide when (and if) action is appropriate. The idea is that agents are not strictly invoked for a task, but activate themselves".

Despite the mention of 'abstraction' in the definition, agents are generally credited with making communication between people and machines easier and more natural than specialized rule languages or knowledge 'templates'.

The definition continues with the different types of agents including ( slightly reformatted for clarity ):

Intelligent agents (in particular exhibiting some aspect of Artificial Intelligence, such as learning and reasoning),

Multi-agent systems (distributed agents that do not have the capabilities to achieve an objective alone and thus must communicate),

Autonomous agents (capable of modifying the way in which they achieve their objectives),

Distributed agents (being executed on physically distinct machines),

Mobile agents (agents that can relocate their execution onto different processors).

Two types of agent, distributed and mobile agents, are classified according to the operating environments where they run.

However, the other three types - intelligent, multi-agent and autonomous agents - are quite different. They have the ability to communicate, reason and learn. In other words, their effectiveness is enhanced by their ability to employ language and knowledge. Particularly, intelligent agents must have extensive rule processing capabilities in order to drive their inferencing capabilities. They see the world from a rule-based perspective,.

There may be an easier way of representing the types of agents listed above by recognizing that the operating environment and degree of agent intelligence are independent.

  Distibuted Mobile
Intelligent agent Intelligent, lives on a server Intelligent, moves between servers
Multi-agent Many simple agents cooperate, lives on a server Many simple agents cooperate, moves between servers
Autonomous Agent behavior not pre-determined, lives on a server Agent behavior not pre-determined, moves between servers


Later, it may be useful to return to the idea of agents as a packaging of semantic services in a form appropriate to different types of knowledge-intensive tasks. For now, what is important is that the Semantic Web Services often use software agents to accomplish specific tasks.


The Vision

There are three important elements to the vision described above.

  • Collecting, processing and exchanging Web content from diverse sources.
  • Interaction between agents increasing the effectiveness of the Semantic Web, that is, it creates a synergy.
  • All agents can work together, even agents who have not been designed to work together.

There seem to be four criteria important in measuring the success of the Semantic Web initiative.

  • Can agents collect, process and exchange web content ?
  • Is there open interaction between agents ?
  • Can alien agents understand each other ?
  • Above all, do agents make communication between people quicker, better and easier ?


The Fuzzy Vision

To what degree has the article's vision of the future been realized in the five years since it was published ? It's difficult to say. To some extent, the definition of the word "Semantic Web" is so loose that it may be futile to try to pin down with certainty whether a particular feature is part of the 'semantic web' application. The answer may be in the eye of the beholder.

Rather than definitions, the next few sections will focus on different, sometimes competing visions of the Semantic Web.