The semantic web provides more context to websites so that not only humans but also machines can interpret the purpose of the content and data on the web to fetch and deliver coherent results.
Why the Semantic Web?
Days of looking through a plethora of books in search of a specific piece of information are long gone. Now all you have to do is click a few words, and voila, google fetches you the results in milliseconds.
We must all appreciate the internet for this time and energy-saving endeavour. However, have you ever wondered about the background process of searching for and retrieving relevant results?
When you type your query, the search engine searches for the relevant keywords. It looks through its entire collection of databases of websites. Then, it compares the keywords with the metadata of the website. Finally, it displays the most relevant results on the first page.
Simple, isn’t it? This technology of adding extra information so machines can offer the end user relevant information is known as the Semantic Web.
What is the Semantic Web?
Tim Berners-Lee, the creator of the World Wide Web, coined the term “semantic web” to describe a novel technology. The Semantic Web is an existing World Wide Web enhancement that allows computer algorithms to access machine-interpretable metadata of posted data and information.
There are a ton of websites with similar names but different purposes on the internet. For instance, if you search for “python” online, you might get two types of results. You might get the reptile’s Wikipedia article or information about the programming language itself.
But with semantic metadata, websites can provide more in-depth keywords to describe the purpose and context of the website. For example, if you are creating a blog to discuss the latest in a python programming language, you can add tags like “python programming language”, “python tutorials”, etc. This way, you convey to the machine that your website is about python programming language.
What are Semantic Web Technologies?
The introduction of the semantic web led to the development of more competent machine understanding. Also, it paved the way for the advancement of artificial intelligence and the Internet of Things.
Artificial intelligence (AI) systems can better grasp language and process information using formal semantics thanks to semantic technology. They can store, manage, and retrieve information in light of meaning and logical linkages. Many companies use semantic technologies and semantic graph databases for the following reasons:
- Managing their content.
- Repurposing and reusing data.
- Decreasing costs.
- Generating new revenue streams.
Semantic technology uses formal semantics to interpret heterogeneous data around the web. In conjunction with Linked Data technology, it establishes connections between data from different sources and formats, from one string to another, aiding in creating context. These raw data points are joined together to create a massive network of data, or knowledge graph, that connects numerous descriptions of items and concepts of general significance.
Primary Standards for Smeantic Technology
The primary standards that Semantic Technology develops upon are:
- RDF (Resource Description Frmaework)
- SPARQL (SPARQL Protocol and RDF Query Language)
- OWL (Web Ontology Language)
RDF is the file format that Semantic Technology utilises to store data in a semantic graph database or on the Semantic Web.
Developers created the semantic query language (SPARQL) to retrieve and process RDF-formatted data from diverse systems and databases.
OWL is a language based on computational logic intended to display data structure, representing rich and complicated information about object hierarchies and their relationships. It is an addition to RDF and enables the formalisation of a data ontology or schema in a certain domain independent of the data.
The main distinction between semantic technology and other data technologies, such as the relational database, is that it focuses on the meaning of the data rather than its form.
The Bottom Line
Though the Semantic Web and its technology may initially seem challenging to understand, the concept itself is not overly complicated. The semantic technologies store data in a way that machines can comprehend, analyse, and will be able to foster a greater understanding of data and content among machines to deliver relevant results to us, users.
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