Semantic Web faces the problem of distributed data head-on. Just as the hypertext Web changed how we think about availability of documents, the Semantic Web is a radical way of thinking about data. At first blush, distributed data seems easy: just put databases all over the Web (data on the Web). But in order for this to act as a distributed web of data, we have to understand the dynamics of sharing data among multiple stakeholders across a diverse world. Different sources can agree or disagree, and data can be combined from different sources to gain more insight about a single topic.
Even within a single company, data can be considered as a distributed resource. Multiple databases, from different business units, or from parts of the business that were acquired through merger or corporate buy-out, can be just as disparate as sources from across the Web. Distributed data means that the data comes from multiple stakeholders, and we need to understand how to bring the data together in a meaningful way.
Broadly speaking, data makes a statement that relates one thing to another, in some way. Copious (one thing) opens (a way to relate to something else) at 5:00pm (another thing, this time a value). They serve (another way to relate to something) chicken and waffles (this time, a dish), which itself is made up (another way to relate) of some other things (chicken, waffles, and a few others not in its name, like maple syrup). Any of these things can be represented at any source in a distributed web of data. The data model that the Semantic Web uses to represent this distributed web of data is called the Resource Description Framework (RDF) and is the topic of Chapter 3.
Features of a Semantic Web
The WWW was the result of a radical new way of thinking about sharing information. These ideas seem familiar now, as the Web itself has become pervasive. But this radical new way of thinking has even more profound ramifications when it is applied to a web of data like the Semantic Web. These ramifications have driven many of the design decisions for the Semantic Web standards and have a strong influence on the craft of producing quality Semantic Web applications.
Give me a voice…
On the WWW, publication is by and large in the hands of the content producer. People can build their own web page and say whatever they want on it. A wide range of opinions on any topic can be found; it is up to the reader to come to a conclusion about what to believe. The Web is the ultimate example of the warning caveat emptor (“Let the buyer beware”). This feature of the Web is so instrumental in its character that we give it a name: the AAA Slogan: “Anyone can say Anything about Any topic.”
In a web of hypertext, the AAA slogan means that anyone can write a page saying whatever they please and publish it to the Web infrastructure. In the case of the Semantic Web, it means that our architecture has to allow any individual to express a piece of data about some entity in a way that can be combined with data from other sources. This requirement sets some of the foundation for the design of RDF.
It also means that the Web is like a data wilderness—full of valuable treasure, but overgrown and tangled. Even the valuable data that you can find can take any of a number of forms, adapted to its own part of the wilderness. In contrast to the situation in a large, corporate data center, where one database administrator rules with an iron hand over any addition or modification to the database, the Web has no gatekeeper. Anything and everything can grow there. A distributed web of data is an organic system, with contributions coming from all sources. While this can be maddening for someone trying to make sense of information on the Web, this freedom of expression on the Web is what allowed it to take off as a bottom-up, grassroots phenomenon.
… So I may speak!
In the early days of the hypertext Web, it was common for skeptics, hearing for the first time about the possibilities of a worldwide distributed web full of hyperlinked pages on every topic, to ask, “But who is going to create all that content? Someone has to write those web pages!”
To the surprise of those skeptics, and even of many proponents of the Web, the answer to this question was that everyone would provide the content. Once the Web infrastructure was in place (so that Anyone could say Anything about Any topic), people came out of the woodwork to do just that. Soon every topic under the sun had a web page, either official or unofficial. It turns out that a lot of people had something to say, and they were willing to put some work into saying it. As this trend continued, it resulted in collaborative “crowdsourced” resources like Wikipedia and the Internet Movie Database (IMDb)—collaboratively edited information sources with broad utility. This effect continued 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
