The past, present, and future of the Internet
The Internet was initially created to share information easily between systems. Nowadays, the Web connects billions of machines worldwide. There exists an ongoing project to create the next generation of the Internet: the Semantic Web. The Semantic Web is a development in which data on the web can be read and understood by machines, with standards proposed by the World Wide Web Consortium (Semantic Web - W3C, 2015)
When Tim Berners-Lee invented the Internet in 1989, he reportedly did so out of frustration (Berners-Lee, 2009). At the time, he was a software engineer at the European Organization for Nuclear Research (CERN) and there existed no standardised means for scientists to share information; files would often be incompatible with one another. He connected two computers and enabled communication between them, via a standardised protocol called HTTP, and the first generation of the Internet was born.
Fast-forward to 2023, and the internet has become vastly more interconnected than what it used to be. Tim Berners-Lee and others have further ambitions about the development of the Internet. This vision of the next generation of the Internet is called the “Semantic Web”, or “Web 3.0”, based on the notion of linked data. The word “semantic” indicates that the data has been structured for machines to infer meaning and relationships between linked data. Here is an excerpt from the W3C website, a consortium aiming at developing the Semantic Web:
The Semantic Web is about two things. It is about common formats for integration and combination of data drawn from diverse sources, where on the original Web mainly concentrated on the interchange of documents. It is also about language for recording how the data relates to real world objects. That allows a person, or a machine, to start off in one database, and then move through an unending set of databases which are connected not by wires but by being about the same thing.
Excerpt from W3C Semantic Web Activity (2012)
The challenge of creating the next generation of the Internet is momentous, and requires experts in every field to create the necessary frameworks and languages to represent complex knowledge about things, groups of things, and relations between things
(OWL - Semantic Web Standards, 2012). No one knows what the Semantic Web will precisely look like, as it will be borne out of the collective efforts of engineers, content creators, and ontologists all over the world. Just as the current version of the Internet, the next generation of the Internet will progressively arise and will be a continuous work in progress. What we do know is that the new Semantic Web holds the promise of much more powerful and meaningful use of data for all existing fields of research and work (Access all areas?, 2001).
In order to contribute to the Semantic Web, data must be structured such that it is interpretable by machines. This has exciting implications for virtually any field, which extend beyond the use of the Internet itself. For instance, in biomedical research, hospitals may use machine learning algorithms to process patients' genomes to uncover correlations between certain genes and diseases (Cyc The Next Generation of Enterprise AI, 2022). When only machine learning algorithms are used, a higher level of noise in the data may hide valuable underlying trends. However, when human knowledge, such as the diagnostic processes of medical doctors, is integrated with the algorithms, this noise may clear to make way for new knowledge.
It may not be immediately obvious to average information-seekers that when they perform a search on the Internet, something called a knowledge graph helps the search engine find what they are looking for (Ontotext, 2020). Currently, knowledge graphs are used for recommendations and answering queries online. The search engine uses keyword search, references from other web pages, the estimated quality of a website and previous queries, among other things, to return content according to (personalised) relevance (Singhal, 2012). However, search engines don't necessarily understand the contents of a given page as part of a search process. With the Semantic Web, the computer will have to be able to access the meaning of the content as part of the search process. For now, a search engine's knowledge graph is able to statistically map links and elements, but not to understand them. We are just at the beginning of the Semantic Web, where structured links between data will become increasingly more meaningful to machines and humans alike.
More about knowledge graphs and how we contribute
The Semantic Web will require machines to communicate with each other, but also incorporate human understanding within the logic of the search engine's processes.
Semantic web representations will require highly expressive knowledge graph structures These higher order types of logic will represent nuances which are currently unavailable in existing knowledge bases and the Internet at large. The collaborations existing within the World Wide Web Consortium develop the ontologies and frameworks that will help organise and nuance human knowledge to machines.