Masterarbeit
Automated REST API Generation for Knowledge Graph Access
Completion
2025/08
Research Area
Intelligent Information Management
Students
Khushbu Mukeshbhai Navdiwala
Advisers
Description
Knowledge Graphs are widely used to represent complex, highly interconnected data in various domains. While SPARQL is a powerful query language for accessing and manipulating data in Knowledge Graphs, many web developers are unfamiliar with it. This creates an obstacle to the adoption of Knowledge Graphs, as many web developers are more accustomed to working with RESTful APIs for accessing data. While automated API code generation techniques exist for relational data structures, there is no widely adopted approach for automatically generating RESTful APIs to access data in Knowledge Graphs.
The objective of this thesis project is to develop a systematic approach to automate the generation of REST APIs that provide access to data within Knowledge Graphs while considering the complexities of graph-based data structures. To this end, the first step is to conduct a requirements analysis and to review the state of the art in (semi-)automatic REST API generation. Existing solutions need to be classified and evaluated according to the identified requirements. Finally, an approach for automatically generating REST APIs for Knowledge Graph access has to be conceptualized, implemented, and evaluated based on the requirements.
