Knowledge Graphs

Chapter 1. Introduction

Graph data has become ubiquitous in the last decade. Graphs underpin everything from consumer-facing systems like navigation and social networks, to critical infrastructure like supply chains and policing. A consistent theme has emerged that applying knowledge in context is the single most powerful tool that most businesses have. Through research and experience, a set of patterns and practices called knowledge graphs has been developed to support extracting knowledge from data.

This report is for information technology professionals who are interested in managing and exploiting data for value. For the CIO or CDO, the report is brief yet thorough enough to provide an overview of the techniques and how they are delivered. For the data professional, data scientist, or software professional, this report provides an easy on-ramp to the world of knowledge graphs, and a language for discussing their implementation with peers and management.

Our fundamental tenet is that knowledge graphs are useful because they provide contextualized understanding of data. They achieve this by adding a layer of metadata that imposes rules for structure and interpretation. We’ll illustrate how using knowledge graphs can help extract greater value from existing data, drive automation and process optimization, improve predictions, and enable an agile response to changing business environments.

This chapter explains the background and motivation behind knowledge graphs. To do so, we’ll ...