smartAPI: Towards a More Intelligent Network of Web APIs

  • Amrapali ZaveriEmail author
  • Shima Dastgheib
  • Chunlei Wu
  • Trish Whetzel
  • Ruben Verborgh
  • Paul Avillach
  • Gabor Korodi
  • Raymond Terryn
  • Kathleen Jagodnik
  • Pedro Assis
  • Michel Dumontier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10250)


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.


Web API Web API description Web services Linked data FAIR principles 



The smartAPI pilot project was funded as a supplement to CEDAR (U41HG000131521). and are supported by U01HG008473 (from NHGRI). The LINCS Data Portal is supported by grant U54HL127624 awarded by the National Heart, Lung, and Blood Institute through funds provided by the trans-NIH LINCS Program and the trans-NIH Big Data to Knowledge (BD2K) initiative


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Amrapali Zaveri
    • 1
    • 2
    Email author
  • Shima Dastgheib
    • 1
  • Chunlei Wu
    • 3
  • Trish Whetzel
    • 4
  • Ruben Verborgh
    • 5
  • Paul Avillach
    • 6
  • Gabor Korodi
    • 6
  • Raymond Terryn
    • 7
  • Kathleen Jagodnik
    • 8
    • 9
    • 10
  • Pedro Assis
    • 11
  • Michel Dumontier
    • 1
    • 2
  1. 1.Stanford Center for Biomedical Informatics ResearchStanford UniversityStanfordUSA
  2. 2.Institute of Data ScienceMaastricht UniversityMaastrichtThe Netherlands
  3. 3.The Scripps Research InstituteSan DiegoUSA
  4. 4.T2 LabsSunnyvaleUSA
  5. 5.Imec – IDLabGhent UniversityGentBelgium
  6. 6.Harvard Medical SchoolBostonUSA
  7. 7.University of Miami, Miller School of MedicineMiamiUSA
  8. 8.Icahn School of Medicine at Mount SinaiNew YorkUSA
  9. 9.NASA Glenn Research CenterClevelandUSA
  10. 10.Baylor College of MedicineHoustonUSA
  11. 11.Department of GeneticsStanford UniversityStanfordUSA

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