as the Web grew to create social networks where a billion people contribute every day, and their contributions come together to become a massive data source with considerable value in its own right.
The hypertext Web grew because of a virtuous cycle that is called the network effect. In a network of contributors like the Web, the infrastructure made it possible for anyone to publish, but what made it desirable for them to do so? At one point in the Web, when Web browsers were a novelty, there was not much incentive to put a page on this new thing called “the Web”; after all, who was going to read it? Why do I want to communicate to them? Just as it isn’t very useful to be the first kid on the block to have a fax machine (whom do you exchange faxes with?), it wasn’t very interesting to be the first kid with a Web server.
But because a few people did have Web servers, and a few more got Web browsers, it became more attractive to have both web pages and Web browsers. Content providers found a larger audience for their work; content consumers found more content to browse. As this trend continued, it became more and more attractive, and more people joined in, on both sides. This is the basis of the network effect: The more people who are playing now, the more attractive it is for new people to start playing. Another feature of the Web that made it and its evolutions possible is the fact that it is auto documented, that is, the documentation for building, using, and contributing to the Web is on the Web itself and when an evolution like the semantic Web comes around, it too can be documented on the Web to support the network effect.
A good deal of the information that populates the Semantic Web started out on the hypertext Web, sometimes in the form of tables, spreadsheets, or databases, and sometimes as organized group efforts like Wikipedia. Who is doing the work of converting this data to RDF for distributed access? In the earliest days of the Semantic Web, there was little incentive to do so, and it was done primarily by vanguards who had an interest in Semantic Web technology itself. As more and more data are available in RDF form, it becomes more useful to write applications that utilize this distributed data. Already there are several large, public data sources available in RDF, including an RDF image of Wikipedia called dbpedia, and a surprisingly large number of government datasets. Small retailers publish information about their offerings using a Semantic Web format called RDFa, using a shared description framework called Schema.org (Section 10.1). Facebook allows content managers to provide structured data using RDFa and a format called the Open Graph Protocol. The presence of these sorts of data sources makes it more useful to produce data in linked form for the Semantic Web. The Semantic Web design allows it to benefit from the same network effect that drove the hypertext Web.
The Linked Open Data Cloud (http://lod-cloud.net/) is an example of an effort that has followed this path. Starting in 2007, a group of researchers at the National University of Ireland began a project to assemble linked datasets on a variety of topics. Figure 1.1 shows the growth of the Linked Open Data Cloud from 2007 until 2017, following the network effect. At first, there was very little incentive to include a dataset into the cloud, but as more datasets were linked together (including Wikipedia), it became easier and more valuable to include new datasets. The Linked Open Data Cloud includes datasets that share some common reference; the web of data itself is of course much larger. The Linked Open Data Cloud includes datasets in a wide variety of fields, including Geography, Government, Life Sciences, Linguistics, Media, and Publication.
Another effort built on these same standards is referred to as knowledge graphs. This name refers to a wide range of information sharing approaches, but the term gained popularity around 2012 when Google announced that it was using something it called a knowledge graph to make searches more intelligent. Google felt that the use of the name Knowledge Graph, instead of something that seemed more esoteric like Semantic Web, would make it easier for people to understand the basic concept. That is rather than a Web of Semantics they would prefer to call it a Graph of Knowledge. The name has caught on, and is now used in industrial settings to refer to the use of Semantic Web technology and approaches in an enterprise setting. The basics of the technology are the same; the standards we outline in this book apply equally well to the Semantic Web, linked data, or knowledge graphs.
What about the round-worlders?
The network effect has already proven to be an effective and empowering way to muster the effort needed to create a massive information network like the WWW; in fact, it is the only method that has actually succeeded in creating such a structure. The AAA slogan enables the network effect that made the rapid growth of the Web possible. But what are some of the ramifications of such an open system? What does the AAA slogan imply for the content of an organically grown web?
Figure 1.1 Number of linked open datasets on the Web in the Linked Open Data Cloud. From the Linked Open Data Cloud at lod-cloud.net.
For the network effect to take hold, we have to be prepared to cope with a wide range of variance in the information on the Web. Sometimes the differences will be minor details in an otherwise agreed-on area; at other times, differences may be essential disagreements that drive political and cultural discourse in our society. This phenomenon is apparent in the hypertext Web today; for just about any topic, it is possible to find web pages that express widely differing opinions about that topic. The ability to disagree, and at various levels, is an essential part of human discourse and a key aspect of the Web that makes it successful. Some people might want to put forth a very odd opinion on any topic; someone might even want to postulate that the world is round, while others insist that it is flat. The infrastructure of the Web must allow both of these (contradictory) opinions to have equal availability and access.
There are a number of ways in which two speakers on the Web may disagree. We will illustrate each of them with the example of the status of Pluto as a planet:
• They may fundamentally disagree on some topic. While the IAU has changed its definition of planet in such a way that Pluto is no longer included, it is not necessarily the case that every astronomy club or even national body agrees with this categorization. Many astrologers, in particular, who have a vested interest in considering Pluto to be a planet, have decided to continue to consider Pluto as a planet. In such cases, different sources will simply disagree.
• Someone might want to intentionally deceive. Someone who markets posters, models, or other works that depict nine planets has a good reason to delay reporting the result from the IAU and even to spreading uncertainty about the state of affairs.
• Someone might simply be mistaken. Web sites are built and maintained by human beings, and thus they are subject to human error. Some web site might erroneously list Pluto as a planet or, indeed, might even erroneously fail to list one of the eight “nondwarf” planets as a planet.
• Some information may be out of date. There are a number of displays around the world of scale models of the solar system, in which the status of the planets is literally carved in stone; these will continue to list Pluto as a planet until such time as there is funding to carve a new description for the ninth object. Web sites are not carved in stone, but it does take effort to update them; not everyone will rush to accomplish this.
While some of the reasons for disagreement might be, well, disagreeable (wouldn’t it be nice if we could stop people from lying?), from a technical perspective, there isn’t any way to tell them apart. The infrastructure of the Web has to be able to cope with the fact that information on the Web will disagree from time to time and that this is not a temporary condition. It is in the very nature of the Web that there be variations and disagreement.
The Semantic Web is often mistaken for an effort to make everyone agree on a single ontology, that is, to make everyone agree on a single set of terms—but that just isn’t the way the Web works. The Semantic Web isn’t about getting everyone to agree, but rather about coping in a world where not everyone will agree and achieving some degree of interoperability anyway. In the data themselves too we may find