Semantic Web

Imagine you are operating a chain of opticians. You need to forecast how a new store might perform under a series of scenarios. All the information is available. Your business has the proposed store details, including its location and size, the expected inventory. External public data, such as regional economics and demographics are available. For you this is not a problem because you have adopted Semantic Web technology that brings all these data together in a single analysis as if it were contained in a single convenient database.

A key part of this technology is the use of Linked Data. In this, hetrogenous data sources are made available via the internet, are cross referenced using Shared Vocabularies and can be related via Ontologies.

Data, Information and Knowledge

The use of ICT to manage information came into prominence thirty years ago with the advent of large scale databases. Data of itself has no meaning; it requires context to convey information. This has historically been provided within the structures of databases and by its presentation in the systems they support. Therefore, if data is removed from its ICT context, then its information content is compromised. To become knowledge, data must carry with it its unambiguous and universal interpretation. Semantic technologies make this possible.

In an information society the preservation of increasing amounts of information is a major cost, and its potential loss an increasing risk. Loss can occur simply because software applications are no longer maintained, or data formats no longer supported. Without action we would eventually face an 'information black hole'.

In a modern knowledge-based economy the effective management of knowledge offers a competitive advantage. The Semantic Web can enable this management.

Linking of Data

Linked Data is about moving towards a true Semantic Web in which related data is connected by virtue of its meaning. This requires no a priori structuring, as in portals; only embedded meaning. It can be achieved simply by adding tags from an agreed vocabulary. For example, a vocabulary for infectious diseases at may unambiguously define the tag virus. Any web page about viruses can embed this tag, semantically linking it to all similarly tagged pages.

Each such knowledge resource is given a unique web identifier, or URI (uniform resource identifier). This allows different data sets to be created in full confidence that two independent sources are referring to exactly the same resource (for example the same virus) irrespective of their own terminology. In more advanced forms of linked data, knowledge is expressed in standard languages and conforms to standards for accessing information about those resources.


Shared knowledge requires more powerful representation mechanisms than simple vocabularies: adding semantics to vocabularies is the purpose of an ontology.

The term ontology was originally used in a branch of philosophy (metaphysics). In this discipline, entities are ordered according to their similarities and differences in categories (also known as concepts) with the resulting conceptual arrangements named ontologies. However, in philosophy categorisations are a prized end point; in Computer Science they are used to add meaning to both tags and to the relationships between tags.

For example, an ontology might define a virus and an infectious disease, and relate these by asserting that a virus is a special kind of infectious disease.


Ontologies can support reasoning. For example, if the description of an innovation that controls infectious disease includes tags from a suitable ontology, it is possible to automatically infer that it might control viruses.

Ontologies that support reasoning are primarily being developed within the natural sciences. Their development is complex and demanding, and only where real advantage can be gained through reasoning can the effort be justified.