The term “Web 2.0” was popularized by Tim O'Reilly and Dale Dougherty at the O'Reilly Media Web 2.0 Conference in late 2004. O'Reilly defined it as not being a change in the technical framework of the Internet but rather a shift in the design and use of websites. The shift was moving away from websites that offered a passive user experience to ones that allowed users a more active experience through the ability to interact and collaborate through social media dialogue and to act as creators of user-generated content.
When I wrote a piece here called "From Web 2.0 to Web 4.0 in December 2019, it was inspired by an article online about "Web 4.0" that made me wonder if we had jumped over Web 3.0.
Web 2.0 websites allowed users to interact and collaborate with each other through social media dialogue as creators of user-generated content in a virtual community. This contrasts the first generation of Web 1.0-era websites where people were limited to viewing the content in a passive manner. Web 2.0 examples include social networking sites or social media sites (Twitter, Facebook, Instagram, Tumblr, et al), blogs, wikis, folksonomies ("tagging" keywords on websites and links), video sharing sites (YouTube, Vimeo), image sharing sites (Pinterest, Flickr), some web apps and any collaborative platforms, and mashups of multiple applications.
World Wide Web inventor Tim Berners-Lee questioned whether Web 2.0 was substantially different from the earlier Web technologies. He said that his original vision of the Web was "a collaborative medium, a place where we [could] all meet and read and write." Berners-lee coined the term "semantic web" at the start of this century, but that has sometimes come to be called Web 3.0. Berners-Lee meant "semantic" to refer to a web of content where the meaning can be processed by machines. (archived version of his article)
Semantics refers to the philosophical study of meaning, but semantics comes up in discussions about search technology. Google, Siri, and Alexa using semantic search technology. In that application, it is the idea of answering user questions rather than merely searching based on a string of keywords. hunt down words. I can ask those applications a question like "What time is sunset tonight?" or "What is the zip code for Montclair, New Jersey?" but I could earlier have asked a search engine "zipcode Montclair NJ" and gotten an answer. Now, when I ask what time is sunset, the app knows where I am and so the answer is location-based.
In 2013, I wrote about Siri and the semantic web and said "We are not at the point where you can ask 'What would I like for dinner tonight?' and expect an answer." That might change as AI plays a larger role in search and other web operations. Semantic search is a data searching technique in which a search query aims to not only find keywords but to determine the intent and contextual meaning of the words a person is using for search.
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