Paper 178 (Research track)

Semi-automatic Alignment of REST APIs to for Effective Service Discovery

Author(s): Simon Schwichtenberg, Stefan Heindorf, Christian Gerth, Gregor Engels

Abstract: Today’s web services are usually REST APIs which are described purely syntactically.
Therefore, an effective service discovery is hindered as service requests and offers are usually heterogeneous with respect to their domain terminologies.
Semantic specifications, based on machine-readable ontologies, allow to overcome this heterogeneity.
However, it means a lot of manual effort to provide semantic specifications by establishing links to an ontology.
In this paper, we present ASTRO, a semi-automatic tool that derives semantic OWL-S specifications from syntactic Open API specifications.
It assists service providers to align their specifications to the widely-adopted ontology in order to reduce heterogeneity.
In our evaluation, we determine the practicality of our approach on a large-scale set of real-world REST APIs from Mashape.
ASTRO considerably reduces manual effort to enrich existing syntactic specifications with semantics.
About 51% of the extracted concepts from Mashape specifications can be mapped to
Based on these enriched specifications, we show that the alignment to improves the effectiveness of the service matchmaker OWLS-MX3 by 61%.

Keywords: Semantics Derivation; Alignment; Domain Ontology;; Web Service; REST API; Heterogeneity; Service Discovery; Mashape

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