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The Knowledge Graph Cookbook

Recipes for Knowledge Graphs that Work

Learn why and how to build knowledge graphs that help enterprises use data to innovate, create value and increase revenue. This practical manual is full of recipes and knowledge on the subject.


Learn more about the variety of applications based on knowledge graphs.

Learn how to build working knowledge graphs and which technologies to use.

See how knowledge graphs can benefit different parts of your organization.

Get ready for the next generation of enterprise data management tools.

Fill out the form to get the book as free PDF or buy the Paperback or Kindle version on Amazon.

Watch the Official Book Presentation!

On-Demand Webinar

Watch Semantic Web Company CEO, Andreas Blumauer and COO, Helmut Nagy at this featured on-demand webinar. On April 22, 2020, they officially released the book to nearly 400 attendees. In this webinar, they explain how the book is a simple guide that makes creating knowledge graphs as easy as cooking your favorite dish.

Why Read This Book?

The Knowledge Graph Cookbook will help you understand how knowledge graphs allow organizations to move from silo-controlled business intelligence based on traditional data warehouses to a holistic approach of augmented intelligence based on a semantic data fabric.

Augmented means that the Human-in-the-Loop (HITL) design principle is applied, in which various interest groups such as subject matter experts (SMEs) or business users engage in a continuous mutual dialogue with AI machines in their daily work, with the knowledge graph becoming the central interface between the various actors in such a system.

The results of this approach are:

  • Higher data quality
  • Reusability of data, e.g., to reduce the effort for data preparation
  • Better interpretability of data and content
  • Automatable processes for integrating and analyzing data
  • Find relevant data, personalize and contextualize it, i.e. integrate it into concrete business processes
  • Use of data for automatic reasoning

The Knowledge Graph Cookbook is a valuable resource for practitioners and decision-makers to take advantage of the many benefits of this methodology, especially the positive impact it has on the implementation of AI strategies.

More About This Book

Knowledge graphs are the ultimate linking engine for the management of enterprise data and drivers for new approaches in artificial intelligence. They are an extremely efficient approach to data governance, metadata management, and data enrichment, and are increasingly being used as data integration technology.

There are countless articles, slide decks and videos on the internet about knowledge graphs. Various standards, methods and technologies are available, but why isn’t there a recipe for how to create a knowledge graph, like there is for baking a pie?

The Knowledge Graph Cookbook explains why your organization should invest in the development of knowledge graphs, and most importantly, what recipes exist for developing and integrating them in an efficient, successful and sustainable way. After reading this book, you will be able to successfully tackle the chaos of contemporary enterprise data management.

By reading The Knowledge Graph Cookbook, you will also learn how contextualized and connected data helps companies achieve higher customer satisfaction or better service levels through holistic views of business objects, for example. You will also learn how knowledge graphs can be used to create reusable data sets that lead to better analytics and training for machine learning algorithms.

The Advantages of Knowledge Graphs

  • Knowledge Graphs (KGs) solve well-known data and content management problems.
  • They are the ultimate linking engine for enterprise data management.
  • They automatically generate unified views of heterogeneous and initially unconnected data sources, such as Customer 360.
  • They provide reusable data sets to be used by analytics platforms or to train machine learning algorithms.
  • They help with the dismantling of data silos. A semantic data fabric is the basis for in-depth analysis.

About The Authors

This book is based on more than 20 years of experience that both authors, Andreas Blumauer and Helmut Nagy, have gathered in the field of semantic technologies, text mining, data management, knowledge management and AI for business use cases.

Andreas Blumauer  is CEO and co-founder of the Semantic Web Company. He is the ‘product architect’ of the PoolParty Semantic Suite and is passionate about knowledge graphs, semantic technologies and machine learning. Since the company was founded 15 years ago, more than 150 organizations have been supported in the use of graph and Semantic AI-based methods and techniques.  

Helmut Nagy is COO of the Semantic Web Company and the team lead of the PoolParty data & knowledge engineering team. Helmut has extensive professional experience in knowledge management and semantic web technologies. He has been working with many Forbes Global 2000 companies on the implementation of Enterprise Knowledge Graphs.