Semantic Technology, as the phrase itself suggests, uses formal semantics to give meaning to all the disparate and raw data that surrounds us. The Semantic Web Technology – or technology for the Web of Data or the Linked Data technology as envisioned by World Wide Web inventor Sir Tim Berners-Lee – builds relationships between data in various formats and sources, from one string to another, helping build context and creating links out of those relationships.
The Semantic Technology defines and links data on the web or within an enterprise by developing languages to express rich, self-describing interrelations of data in a form that machines can process. Thus, machines are not only able to process long computing strings of characters and index tons of data, but they are also able to store, manage and retrieve information based on meaning and logical relations. Semantics adds another layer to the web and is able to show related factsitems instead of just word matching.
The principal technologies of the Semantic Technology, the semantic graph database for example, use a set of universal standards, as set down by the World Wide Web Consortium (W3C) international community that develops open standards.
“The core difference between Semantic Technologies and other technologies for data, the relational database for instance, is that the Semantic Technology deals with the meaning rather than the structure of the data.
W3C’s Semantic Web initiative states that the purpose of this technology in the context of the semantic web to create a ‘universal medium for the exchange of data’ by smoothly interconnecting the global sharing of any kind of personal, commercial, scientific and cultural data. W3C has developed open specifications for the semantic technology developers to stick to and has identified, via open source development, the infrastructure parts that will be needed to scale in the Web, and applicable elsewhere.
In terms of Semantic Technology, the standards that apply are primarily the Resource Description Framework (RDF), SPARQL (SPARQL Protocol and RDF Query Language), and optionally OWL (Web Ontology Language).
Using all those standards, the Semantic Technology makes life easier by helping computers help us how to find the right data piece right away and how to filter items to create more value.
Semantic Technology helps users and enterprises discover smarter data, infer links and extract knowledge from enormous sets of raw data in various formats and from various sources. The Semantic Web, let’s say that a technology such as GraphDB , makes data content easier for machines to integrate, find, access, retrieve, process and automate. This, in turn, enables organizations to gain faster and more cost-effective access to meaningful and accurate data, to analyze that data and turn it into knowledge. Then they can further use that knowledge to gain insights, apply predictive models and make data-driven decisions.
Various businesses are already using semantic technologies and graph databases to manage their content, repurpose and reuse information, cut costs and gain new revenue streams. The BBC, FT and Elsevier use semantic publishing; in healthcare and life sciences Astra Zeneca also uses semantic technology. The financial industry and insurance companies have also started adopting technologies to semantically enrich content and access and process complex and heterogeneous data. E-commerce, the automotive industry, the government and public sector, technology providers, the energy sector, the services sector, among others, are also employing semantic technology developers to extract knowledge from data by attributing meaning to various datasets.
As early as in 2007, Sir Berners-Lee told Bloomberg “The Semantic Technology isn’t inherently complex. The Semantic Technology language, at its heart, is very, very simple. It’s just about the relationships between things.”
Chances are that the ‘relationships between things’ will make the lives of all users easier and will help organizations manage data more efficiently to create more and more smarter data and gain more value.