LDflex: a Read/Write Linked Data Abstraction for Front-End Web Developers

In Proceedings of the 19th International Semantic Web Conference (2020)

Many Web developers nowadays are trained to build applications with a user-facing browser front-end that obtains predictable data structures from a single, well-known back-end. Linked Data invalidates such assumptions, since data can combine several ontologies and span multiple servers with different APIs. Front-end developers, who specialize in creating end-user experiences rather than back-ends, need an abstraction layer to the Web of Data that matches their existing mindset and workflow. We have developed LDflex, a domain-specific language that exposes common Linked Data access patterns as concise JavaScript expressions. In this article, we describe the design and embedding of the language, and discuss its daily usage within two companies. LDflex succeeds in eliminating a dedicated data layer for common and straightforward data access patterns, without striving to be a replacement for more complex cases. Our experiences reveal that designing a Linked Data developer experience—analogous to a user experience—is crucial for adoption by the target group, who can create Linked Data applications for end users. Crucially, simple abstractions require research to hide the underlying complexity.