We have often wondered how it is possible that one day, computer data can be processed semantically, that is, how the code itself interprets itself and can interact with other data without human intervention.
Originally, the web, called Web 1.0, arose from the need to exchange information. On the other hand, the well-known Web 2.0 is characterized because users are the ones who produce and exchange content; it is a social website.
Hence, thanks to the Internet, we are in a historic moment: humanity had never had so much written or audiovisual content and had such immediate access. Web 3.0 is characterized by 3D (augmented reality), Geolocation, and Artificial Intelligence (semantic web). We are going to dwell on this last feature. In the Master in Data Analysis and Artificial Intelligence, you learn all these concepts and many more.
What is the Semantic Web?
The semantic web is an extension of the World Wide Web (WWW), which seeks to improve how information is structured, linked, and understood by humans and machines.
Its main purpose is to allow computers to understand the meaning of information on the web rather than simply displaying it as text or raw data.
Tim Berners-Lee, one of the creators of the WWW, pioneered the idea of the semantic web.
The semantic web has several advantages and applications, including:
- Smarter search: Allows search engines to better understand queries and provide more accurate and relevant results.
- Data integration: Facilitates combining and enriching data from various sources since machines can automatically interpret and relate the information.
- Interoperability: Allows different systems and applications to communicate and share data more effectively.
- Knowledge representation: Facilitates the creation of systems that can reason and make decisions based on structured knowledge.
- Task automation: By allowing machines to understand and process information, certain tasks and processes can be automated.
What is the Semantic Web?
Instead of simply connecting documents through hypertext links, the semantic web proposes associating data with well-defined meaning through metadata and ontologies.
This metadata provides information about the content and context of the data, allowing machines to interpret and relate the information more intelligently.
The semantic web uses special markup languages such as RDF (Resource Description Framework), which allows describing resources and their relationships through triplets of the form subject-predicate-object.
WOL (Web Ontology Language) is also used to define ontologies, formal models representing knowledge in a specific domain, and the relationships between concepts.
10 Success Stories of Companies that Apply the Semantic Web
Various companies and organizations in different industries have adopted the semantic web to improve the understanding and management of data.
Google uses semantic web techniques to improve the relevance of search results and provide more accurate answers to user queries. Adopting structured markup schemes like Schema.org has allowed Google to better understand content and present rich snippets and graphical insights in its search results.
Amazon
The company uses the semantic web to recommend products to users based on their preferences and purchasing behavior. Semantic data helps them analyze buying patterns and create personalized and accurate recommendations.
IBM Watson
IBM Watson is an artificial intelligence and semantic web-based system successfully applied in various industries, including healthcare, finance, and help desks.
Watson can analyze large amounts of unstructured data and provide answers and recommendations based on insights drawn from semantic sources.
BBC
The British Broadcasting Corporation (BBC) uses semantic web technologies to improve the presentation and organization of its content. The BBC can offer users a richer and more personalized browsing experience using ontologies and metadata.
The social network Facebook has used semantic web techniques to improve the relevance of its news feed and personalize the content displayed to users. It also uses RDFa and other semantic markup methods to enrich the information shared on its platform.
Siemens
Siemens uses the semantic web for knowledge management and data integration in different sectors, such as industry, energy, and healthcare. Semantic techniques allow a better understanding and use of information in their systems and processes.
AstraZeneca
This pharmaceutical company has used the semantic web to improve drug research and development. Integrating data from different sources and semantic analysis have accelerated drug discovery.
Wolfram Alpha
Wolfram Alpha is a semantic web-based knowledge engine that answers direct questions from users. It uses ontologies and a large database to offer structured and relevant information.
Elsevier
The scientific publisher Elsevier has embraced the semantic web to improve search and access to articles and research data. Using metadata and semantic links facilitates researchers’ identifying and retrieving relevant information.
Google Knowledge Graph
Google Knowledge Graph is a semantic database that provides additional information about people, places, and things related to a search query. This allows Google to offer more precise and rich answers in its search results.
