Been along follower of semantic Webs, that is webs that aim to capture and readily make usable human, corporate and systems knowledge. It forms the background of things like a knowledge graph. Been involved now in several attempts to mine and store the knowledge of parts of corporate knowledge and including related process knowledge. Even a example of RPA linked process. I have to say that none of these efforts was completely successful. That is ending up as a ongoing way to create, store and test substantial knowledge in context. Have talked about this frequently here. Still we learned much. But why not? Still a student of the practice. Reading this piece, hopefully to better understand why. Will try to revisit the journey here. - FAD
A Review of the Semantic Web Field, By Pascal Hitzler
Communications of the ACM, February 2021, Vol. 64 No. 2, Pages 76-83 10.1145/3397512
Let us begin this review by defining the subject matter. The term Semantic Web as used in this article is a field of research rather than a concrete artifact—in a similar way, say, Artificial Intelligence denotes a field of research rather than a concrete artifact. A concrete artifact, which may deserve to be called "The Semantic Web" may or may not come into existence someday, and indeed some members of the research field may argue that part of it has already been built. Sometimes the term Semantic Web technologies is used to describe the set of methods and tools arising out of the field in an attempt to avoid terminological confusion. We will come back to all this in the article in some way; however, the focus here is to review the research field.
This review will be rather subjective, as the field is very diverse not only in methods and goals being researched and applied, but also because the field is home to a large number of different but interconnected subcommunities, each of which would probably produce a rather different narrative of the history and the current state of the art of the field. I therefore do not strive to achieve the impossible task of presenting something close to a consensus—such a thing still seems elusive. However, I do point out here, and sometimes within the narrative, that there are a good number of alternative perspectives.
The review is also very selective, because Semantic Web is a rich field of diverse research and applications, borrowing from many disciplines within or adjacent to computer science. In a brief review like this one cannot possibly be exhaustive or give due credit to all important individual contributions. I do hope I have captured what many would consider key areas of the Semantic Web field. For the reader interested in obtaining a more detailed overview, I recommend perusing the major publication outlets in the field: The Semantic Web journal,a the Journal of Web Semantics,b and the proceedings of the annual International Semantic Web Conference.c This is by no means an exhaustive list, but I believe it to be uncontroversial that these are the most central publication venues for the field.
Now that we understand that Semantic Web is a field of research, what is it about? Answers to this question are again necessarily subjective as there is no clear consensus on this in the field.
One perspective is that the field is all about the long-term goal of creating The Semantic Web (as an artifact) together with all the necessary tools and methods required for creation, maintenance, and application. In this particular narrative, The Semantic Web is usually envisioned as an enhancement of the current World Wide Web with machine-understandable information (as opposed to most of the current Web, which is mostly targeted at human consumption), together with services—intelligent agents—utilizing this information. This perspective can be traced back to a 2001 Scientific American article,1 which arguably marks the birth of the field. Provision of machine understandable information in this case is done by endowing data with expressive metadata for the data. In the Semantic Web, this metadata is generally in the form of ontologies, or at least a formal language with a logic-based semantics that admits reasoning over the meaning of the data. (Formal metadata is discussed later.) This, together with the understanding that intelligent agents would utilize the information, perceives the Semantic Web field as having a significant overlap with the field of Artificial Intelligence. Indeed, for most of the major artificial intelligence conferences held in the last 20 years ran explicit "Semantic Web" tracks. ... "
