4.16 Technologies and explicit knowledge continued
4.16.1 Ontologies + the Web = the Semantic Web
Tim Berners-Lee, the inventor of the World Wide Web, has defined a vision of the Web's evolution into the Semantic Web:
The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation. The first steps in weaving the Semantic Web into the structure of the existing Web are already under way. In the near future, these developments will usher in significant new functionality as machines become much better able to process and ‘understand’ the data that they merely display at present.
The key idea is that, while Web pages started out being designed by and for humans, there are situations where they could be usefully interpreted by computers, if there were structured descriptions of them using ontology-based metadata. The HyperText Markup Language (HTML) is the simple mark-up scheme on which much of the World Wide Web is based to date, for human interpretation. The Extensible Markup Language (XML), coordinated by the World Wide Web Consortium, makes it easy for an organisation to define new kinds of tags and document types that reflect its concerns. This unit, for example, is rendered in HTML and is also available as an XML file to download in the. An ontology web language such as OWL constrains the XML markup terms so that their meaning can be controlled, and some forms of automated reasoning can be done.
Computers will be able to read formally codified information attached to web pages (for example, in XML format) to reason and search. There is now an enormous amount of activity to realise this vision, both in business (there are many e-business and knowledge management applications) and research (for example, a further step towards a global library). Ontologies, as introduced above, offer one way to automatically resolve ambiguities about the meaning of such formally codified information – there can now be a pointer to the ontology from which a resource's vocabulary is taken. Software agents (introduced below) are programs that will be better enabled by ontologies to collect, analyse and share information semi-autonomously.
An important distinction to grasp is that there will not be a single Semantic Web, analogous to the Web we have today. Analogous to the ‘islands of local coherence’, referred to when we discussed mapping knowledge across communities of practice, there will be many Semantic Webs, each one being a set of websites and ontologies which its users trust, and have built systems to use.
How does the use of formal ontologies relate to perspectives such as situated action, tacit knowledge, communities of practice and boundary objects? Is there a contradiction in embedding codified knowledge models in systems (which seek to systemise and control meaning), while also subscribing to social, situated conceptions of knowledge (which emphasise that meaning is context dependent)?
Ontologies are used to control interpretation, to avoid misunderstandings and confusions. This is fine for machine-machine communication (for example, software agents), but enforcing their use for communication between people can, of course, be harder. Language is a slippery thing. Effective use of a controlled vocabulary is more likely to be possible within a community of practice, since the ontology's terminology and perspective may not correspond to the interests, perspectives or concerns of other communities of practice. Another way of putting this is that ontologies require consensus on what should be included and how it should be structured.
Ontologies (and the knowledge-based systems which implement them) are expensive to design in terms of intellectual and development effort, and so are more cost-effective for representing stable aspects of the world that are unlikely to radically change their structure.
While an operational knowledge-based system can only be used in a well-understood domain, the process of trying to construct informal, ‘disposable’ ontologies can be illuminating. Rough outlines and concept maps focus attention on what counts as an important distinction. If different communities of practice are involved, these can therefore serve as a boundary object to uncover assumptions.