SmartAPI: Towards a more intelligent network of web APIs

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Abstract

Data science increasingly employs cloud-based Web application programming interfaces (APIs). However, automatically discovering and connecting suitable APIs for a given application is difficult due to the lack of explicit knowledge about the structure and datatypes of Web API inputs and outputs. To address this challenge, we conducted a survey to identify the metadata elements that are crucial to the description of Web APIs and subsequently developed the smartAPI metadata specification and associated tools to capture their domain-related and structural characteristics using the FAIR (Findable, Accessible, Interoperable, Reusable) principles. This paper presents the results of the survey, provides an overview of the smartAPI specification and a reference implementation, and discusses use cases of smartAPI. We show that annotating APIs with smartAPI metadata is straightforward through an extension of the existing Swagger editor. By facilitating the creation of such metadata, we increase the automated interoperability of Web APIs. This work is done as part of the NIH Commons Big Data to Knowledge (BD2K) API Interoperability Working Group.

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APA

Zaveri, A., Dastgheib, S., Wu, C., Whetzel, T., Verborgh, R., Avillach, P., … Dumontier, M. (2017). SmartAPI: Towards a more intelligent network of web APIs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10250 LNCS, pp. 154–169). Springer Verlag. https://doi.org/10.1007/978-3-319-58451-5_11

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