To understand the principle behind how the Semantic Web evolved, imagine a jukebox. This classic machine plays the song a patron selects through the push of buttons.
This transformation is making the web much more dynamic, allowing not only content, but also data, to travel freely and seamlessly. We must make our content "semantic", or annotated with meaningful metadata and relationships, to transform dull and dormant fixed-text into live and electric linked concepts. The applications of the Semantic Web are endless, but we cannot take advantage of these possibilities until we have a truly intelligent web of global knowledge. This could be possible by gathering and connecting disparate data published on the web, like information that nearby venues post online, and matching it to the data about the type of music a user has chosen to share on their online playlists. For example, with semantically connected and described data, a digital assistant could send users local live music recommendations in their area. The Semantic Web not only improves traditional search, but it is facilitating more seamless, intelligent, and integrated customer experience journeys as well. Because of this rich, new layer of information, search engines and other bots are able to provide the most relevant content directly to the user, edited to the most important snippets that save humans time and effort.
We can see the application of semantic data in various places throughout the web, such as those in certain search experiences. When such machine-readable descriptions are present, they can be linked to build a more robust web of data where computers can find, read, and even reason about a unit of content. These elements are then assigned a “label” describing its meaning in a standardized language. Adopting Semantic Web approaches to content gets publishers closer to globally-machinable sets of content.Įngineering the Semantic Web Content engineers are creating a more powerful and agile web of content and data by first parsing and structuring the discrete elements of content that constitute websites, such as people, events, ideas, concepts, products. AI will always remain niche applications built against a limited corpus of content until structure and semantic standards exist across content sets. Semantic Web content structures form an essential basis for a reliable graph, or map of knowledge, necessary for true artificial intelligence (AI) beyond basic Natural Language Processing (NLP) and Natural Language Understanding (NLU).
Semantic standards unlock a crucial evolution of the web towards intelligence that allows the content we post online to be presented in a way that can be understood, connected, and remixed by machines. The Semantic Web leads to smarter, more effortless customer experiences by giving content the ability to understand and present itself in the most useful forms matched to a customer’s need.
The Semantic Web is the knowledge graph formed by combining connected, Linked Data with intelligent content to facilitate machine understanding and processing of content, metadata, and other information objects at scale.