GraphQL schema generation for data-intensive web APIs

Sharing data as a (non-)commercial asset on the web is typically performed using an Application Programming Interface (API). Although Linked Data technologies such as RDF and SPARQL enable publishing and accessing data on the web, they do not focus on mediated and controlled web access that data providers are willing to allow. Thus, recent approaches aim at providing traditional REST API layer on top of semantic data sources. In this paper, we propose to take advantage of the new GraphQL framework that, in contrast to the dominant REST API approach, exposes an explicit data model, described in terms of the so-called GraphQL schema, to enable precise retrieving of only required data. We propose a semantic metamodel of the GraphQL Schema. The metamodel is used to enrich the schema of semantic data and enable automatic generation of GraphQL schema. In this context, we present a prototype implementation of our approach and a use case with a real-world dataset, showing how lightly augmenting its ontology to instantiate our metamodel enables automatic GraphQL schema generation.Peer ReviewedPostprint (author's final draft

Task-Relevant API Development for Higher Education Using GraphQL

To develop applications that support a variety of campus needs, North Dakota State University's Enterprise Application Development team requires a method of accessing North Dakota State University System data related to university students, faculty, and staff. As state requirements limit direct access to this data, and conventional API access methods are not well-suited to application use cases, this paper will explore how the data is acquired, stored, and then made accessible to individual applications using GraphQL. A single application, Graduate Waiver Wire, is presented as a use case depicting how GraphQL aids in the automatic data update process, freeing the time previously spent by Graduate School personnel in manually updating graduate student information

GraphQL schema generation for data-intensive web APIs

Sharing data as a (non-)commercial asset on the web is typically performed using an Application Programming Interface (API). Although Linked Data technologies such as RDF and SPARQL enable publishing and accessing data on the web, they do not focus on mediated and controlled web access that data providers are willing to allow. Thus, recent approaches aim at providing traditional REST API layer on top of semantic data sources. In this paper, we propose to take advantage of the new GraphQL framework that, in contrast to the dominant REST API approach, exposes an explicit data model, described in terms of the so-called GraphQL schema, to enable precise retrieving of only required data. We propose a semantic metamodel of the GraphQL Schema. The metamodel is used to enrich the schema of semantic data and enable automatic generation of GraphQL schema. In this context, we present a prototype implementation of our approach and a use case with a real-world dataset, showing how lightly augmenting its ontology to instantiate our metamodel enables automatic GraphQL schema generation.Peer Reviewe