• DocumentCode
    125333
  • Title

    A Graph-Based Data Model for API Ecosystem Insights

  • Author

    Wittern, Erik ; Laredo, Jim ; Vukovic, Maja ; Muthusamy, Vinod ; Slominski, Aleksander

  • Author_Institution
    eOrganization Res. Group, Res. Center for Inf. Technol., Berlin, Germany
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    41
  • Lastpage
    48
  • Abstract
    APIs are increasingly important for companies to enable partners and consumers to access their services and resources. API ecosystems deal with related challenges like publication, promotion and provision of APIs by providers and identification, selection and consumption of APIs by consumers. To address these challenges, to match consumers with relevant APIs, and to support API providers and thus ultimately the ecosystem to evolve, API ecosystems rely on information about APIs, their usage and characteristics, and the social environment around them. We present an extensible, graph-based data model to capture the entities in an API ecosystem and their relations. The data model includes temporal information to capture the evolution of API ecosystems. Analysis operations on top of the data model provide insights for consumers, providers and the ecosystem provider to address the introduced challenges. We present a system implementing the conceptualized data model. We integrate this system with an API ecosystem used in the context of a hackathon event to continuously collect data. We furthermore show the data model´s capabilities to represent a well-known dataset about ProgrammableWeb and to drive analysis operations on both datasets.
  • Keywords
    application program interfaces; data models; graph theory; API ecosystem; API providers; ProgrammableWeb; conceptualized data model; graph-based data model; social environment; temporal information; Companies; Data collection; Data models; Ecosystems; Resource description framework; Web services; API ecosystem; RDF; data model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Services (ICWS), 2014 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5053-9
  • Type

    conf

  • DOI
    10.1109/ICWS.2014.19
  • Filename
    6928879