Semantic Web

Semantic Web

 The Semantic Web is a vision for linking data across webpages, applications and files. Some people consider it part of the natural evolution of the web, in which Web 1.0 was about linked webpages, Web 2.0 was about linked apps and Web 3.0 is about linked data. It was actually part of computer scientist Tim Berners-Lee's original plan for the World Wide Web but was not practical to implement at scale at the time.

The grand vision is that all data will someday be connected in a single Semantic Web. In practice, today's semantic webs are fractured across specialized uses, including search engine optimization (SEO), business knowledge management and controlled data sharing.

In SEO, all major search engines now support Semantic Web capabilities for connecting information using specialized schemas about common categories of entities, such as products, books, movies, recipes and businesses that a person might query. These schemas help generate the summaries that appear in Google search results.

In the case of business knowledge management, companies can use various tools to curate a semantic network (knowledge graph), a graphical representation of entities and their relationships, from information scraped from corporate documents, business services and the public web. This can improve planning, analysis and collaboration in the organization.

The future of the Semantic Web

An increasing number of websites automatically add semantic data to their pages to boost search engine results. But there is still a long way to go before data about things is fully linked across webpages. Translating the meaning of data across different applications is a complex problem to solve.

Innovations in AI and natural language processing might help bridge some of these gaps, particularly in specific domains like skill taxonomies, contract intelligence or building digital twins. Increasingly, the future may involve a hybrid approach combining better governance of the schemas an organization or industry uses to describe data and AI and statistical techniques to fill in the gaps. Getting closer to the original vision of a web of connected data will require a combination of better structure, better tools and a chain of trust.