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Linked REST APIs: A Middleware for Semantic REST API Integration

Authors: Diego Serrano; Eleni Stroulia; Diana H. Lau; Tinny Ng;

Linked REST APIs: A Middleware for Semantic REST API Integration

Abstract

Over the last decade, an exponentially increasing number of REST services have been providing a simple and straightforward syntax for accessing rich data resources. To use these services, however, developers have to understand "information-use contracts" specified in natural language, and, to build applications that benefit from multiple existing services they have to map the underlying resource schemas in their code. This process is difficult and error-prone, especially as the number and overlap of the underlying services increases, and the mappings become opaque, difficult to maintain, and practically impossible to reuse. The more recent advent of the Linked Data formalisms can offer a solution to the challenge. In this paper, we propose a conceptual framework for REST-service integration based on Linked Data models. In this framework, the data exposed by REST services is mapped to Linked Data schemas, based on these descriptions, we have developed a middleware that can automatically compose API calls to respond to data queries (in SPARQL). Furthermore, we have developed a RDF model for characterizing the access-control protocols of these APIs and the quality of the data they expose, so that our middleware can develop "legal" compositions with desired qualities. We report our experience with the implementation of a prototype that demonstrates the usefulness of our framework in the context of a research-data management application.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
16
Top 10%
Top 10%
Top 10%
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