about updating the material.
Until one day, it was Fabien Gandon who asked the question. Jim told him that we were both over-committed, and hinted that perhaps what we needed was a third author, to bring a new viewpoint and energy to the project. With a little bit of arm-twisting, Fabien agreed to take on that role. So we welcome Fabien as a new author. Without his energy and initiative, this project would never have happened.
In writing this edition, we realized that the experiences we have gained, both positive and not, in working on real projects for government and industry, as well as in large academic networks, had helped us to develop a more mature understanding of what role the Semantic Web stack really can play in much larger scale projects. Further, we have been seeing the role of semantics on the web not just expand, but become crucial to the modern web ecosystem which increasingly includes artificial intelligence, large-scale E-commerce, and an increasing ubiquity of knowledge graph systems. The new examples and modeling techniques discussed in this edition, are motivated by many of the projects we have been involved with that required bringing together many disparate datasets or providing structure to the extracted information from the vast web of unstructured text, which power so much of the machine-learning-based techniques that are crucial to modern enterprises.
There are a number of innovations in the third edition. The biggest addition is a whole chapter on Linked Data, brought in primarily by Fabien, with an emphasis on the Web Architecture behind the Semantic Web. We also revisited all of the examples, and where necessary, brought them up to date. New versions of CHEBI and QUDT have been released since our second edition, and the Good Relations ontology has been absorbed into the larger Schema.org effort (Chapter 14 in this edition). We have updated the examples from data.gov. In this case, there were changes to how data are published (some data sets that were previously published in RDF no longer are), but also changes to technology (the methods for importing tabular data as RDF that we outlined in earlier editions are now available as web services, so there is no longer any need for data publishers to perform RDF conversions themselves.).
We have updated our modeling advice (Chapters 15 and 16), based on experience working on ontologies in the Semantic Web and informed by new insights brought in by Fabien. We have added a small section about BridgeDB, a simple application of Linked Data principles to life sciences. We have updated Chapter 11 to reflect changes in The AGROVOC vocabulary since the second edition.
Probably the most common inquiry we got about the second edition was a request for the data behind the examples in the book. We got requests to host them in GitHub, so that anyone could download them, but this isn’t a very exciting way to distribute example data for a book like this. A download of the data requires students to install their own semantic database to run the queries in the book.
We are happy to announce that for the third edition, all the datasets are available on the workingontologist.org website, not just for download (which they are), but also all the queries are available as well, in runnable form. That is, you can look up any query in the book, and run it against the data, and get the same answer you see in the book. Furthermore, you can make your own copy of the query and try variations to see how it works. The examples in the book have all come alive.
We hope that we can build a community of students who take the data from this edition and make it their own; add new queries, new ideas and even new data, so that the examples in the book become a seed for a growing set of examples and data to inspire a new generation of Semantic Web students.
Acknowledgments
In the time between the second and third editions, there have been a number of industrial deployments of the Semantic Web stack, which have informed our treatment of the material. The adoption of the technology in industry is what drove, to a large extent, the motivation to release a third edition at all.
As we have updated the examples for QUDT, we’d like to acknowledge the help we received from Steve Ray to coordinate the second edition of QUDT with the examples in the book. Without his help, our examples would be out of date as soon as the book hit print. From Schema.org, we’d like to acknowledge Eric Franzon, who helped us to coordinate the motivation for Schema.org with the principles of Semantic Web and Linked Data that we describe in this book. We’d like to acknowledge the leadership at the Enterprise Data Management (EDM) Council for their assistance with the FIBO examples, and the leadership at the United Nations Food and Agriculture Organization (FAO) and Global Open Data for Agriculture and Nutrition (GODAN) for their work on AGROVOC.
All of the figures in the third edition were built using the open-source Cytoscape platform, using a plug-in for data.world. We are grateful to Bryon Jacob of data.world for all the work he put in to tailoring the Cytoscape connection to the needs of this book. We also want to thank data.world for hosting all the data and queries in the book, so that we can check that all the answers are correct.
We’d like to thank Tim Beers for copy editing the manuscript before delivering it to the publisher. It is impossible to copy edit your own writing, so having a fresh pair of eyes was invaluable. We also thank Michele Murray and Jacky Carley of RPI who provided crucial logistic and administrative support for Jim as he worked on this edition.
Finally, and most importantly, we’d like to thank all the students and readers who have encouraged us over the past decades. The project managers who encouraged their programmers to read the book, the readers who wrote to us pointing out errata, and everyone who has told us that they read and appreciated the previous books have encouraged us to put the effort into this third edition.
1 What Is the Semantic Web?
This book is about something we call the Semantic Web. From the name, you can probably guess that it is related somehow to the World Wide Web (WWW) and that it has something to do with semantics. Semantics, in turn, has to do with understanding the nature of meaning, but even the word semantics has a number of meanings. In what sense are we using the word semantics? And how can it be applied to the Web?
This book is for a working ontologist. An ontologist might do their work as part of an Enterprise Knowledge Graph, a data lake, global linked data, graph data, or any of a number of other technological approaches that share the idea that data is more powerful when it comes together in a meaningful way. The aim of this book is not to motivate or pitch the Semantic Web but to provide the tools necessary for working with it. Or, perhaps more accurately, the World Wide Web Consortium (W3C) has provided these tools in the forms of standard Semantic Web languages, complete with abstract syntax, model-based semantics, reference implementations, test cases, and so forth. But these are like any tools—there are some basic tools that are all you need to build many useful things, and there are specialized craftsman’s tools that can produce far more specialized outputs. Whichever tools are needed for a particular task, however, one still needs to understand how to use them. In the hands of someone with no knowledge, they can produce clumsy, ugly, barely functional output, but in the hands of a skilled craftsman, they can produce works of utility, beauty, and durability. It is our aim in this book to describe the craft of building Semantic Web systems. We go beyond only providing a coverage of the fundamental tools to also show how they can be used together to create semantic models, sometimes called ontologies or vocabularies, that are understandable, useful, durable, and perhaps even beautiful.
1.1
