Semantic Web techniques

The Semantic Web has been described as a deep and vast blue ocean of opportunity to improve the creation and consumption of data.
It can also help to think of it as a Customer Relationship Management tool which expands the value of data for people, places and organisations around a specific domain of knowledge. This can be dynamically classified and managed to deliver information through search and discovery.

At its core the value of applying Semantic Web techniques accrues through the automation of the processes which make structured information available. (This addresses problems with the volume, variability, velocity and veracity of existing and legacy data.)
Structuring the information improves the value of data to the users of the data, and delivers efficiencies in how data can be managed, curated and consumed. This aids research; shaping the user experience and engagement with data; and, creates an opportunity to increase the efficiency of knowledge workers.

The creation of knew products and services can be readily investigated and developed allowing organisations to innovate with data.

As with a CRM it seeks to describe and manage the relationships between consumers and customers of data by providing insights which lead to improvements in existing processes and services as well as new product development.

Key Features

  • augments existing data allowing direct curation and classification of knowledge by 'domain, 'person', 'organisation' and 'location' or custom categories based on specific ontologies, allowing data to be both productised, distributed and discovered.
  • provides an ecosystem for the acquisition consumption and redistribution of knowledge through automated services that provide efficiency savings for data and quality management.
  • flexible integration with Content Management or Document Management Systems or services accessible for end-users via RESTful interfaces through cloud based services.
  • resulting output may be made available to a range of devices.
  • construction and deployment of an ontology to reference data.


The value of an ontology accrues from its description of concepts and relationships across a domain of knowledge, for example SNOMED CT. This allows consistent and coherent communication between 'agents', programming languages, software applications and operating systems. It is descriptive yet agnostic; and can be shared. Agents can use it to search and discover content across multiple stores of data.