Thomas Frisendal - Visual Design of GraphQL Data: A Practical Introduction with Legacy Data and Neo4j

Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the book's product page, located at www.apress.com/9781484239032 . For more detailed information, please visit http://www.apress.com/source-code .

You know the basics of GraphQL, but you are still uncertain about how to get business content and API structures right in GraphQL?

GraphQL is indeed an attractive data API for applications (and people).

The GraphQL Schema is pivotal to the success of a GraphQL API. Most development projects involve many stakeholders. There are the developers, of course, and there are business experts as well as application owners, who are to consume the content of the API. This means that the schema is not only a scope contract, but also the authoritative source of structure and meaning of the context covered by the API. There are many other contexts, where complex structures and semantics must be communicated effecetively between a number of people with various backgrounds. And the trick invariably turns out to be: Use good visualizations!

The main proposition of this book is graph visualization: GraphQL Schema structure and meaning must be visualized, and the book shows you how. Since the schema is a data graph containing related concepts in a network organized as a directed graph, the increasingly popular property graph paradigm is very appropriate for visualizing GraphQL structures and semantics.

The second theme of this book is that of quality. GraphQL APIs can be used in many constellations possibly including legacy data and/or externally sourced data. Quality must be ensured in all cases. Both on the definitional level (business terminology etc.) and on the data content level (meaningful presentation of the data in business-friendly formats). The book summarizes the top 10 most important focal areas of such quality assurance remedies.

In this manner, the (data and metadata quality) challenges of front-ending old and new databases with a GraphQL API is the third theme of this book.

The book contains simple guidelines based on lessons learned from real life data discovery and unification. This helps developers and architects to get good quality in the resulting API designs. And the visual techniques helps in producing convincing visual communication about the structure of the API designs.

Spending time on schema quality means that developers work from sharp definitions, which in turn leads to greater productivity and well-structured applications.

Named relationships is one of the fundamental recommendations of this book. The importance of this was made originally by Prof. Joseph D. Novak, who was one of the fathers of Concept Mapping in the development of the psychology of learning.

GraphQL is designed by Facebook, Copyright 2015-2016. It is now an open source project, where the software is available under a BSD 3 license. Refer to for more information.

The GraphQL @relation schema directive originated at Graphcool, refer to for more information.

The chapter about using GraphQL with a new graph database draws heavily on a blogpost . I am quoting from it with the authors kind permission. Thank you!