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http://repositorio.grial.eu/handle/grial/1063
Title: | Improving the OEEU’s data-driven technological ecosystem’s interoperability with GraphQL |
Authors: | Vázquez-Ingelmo, A. Cruz-Benito, Juan García-Peñalvo, Francisco J. |
Keywords: | GraphQL API Technological ecosystems Data-driven Interoperability |
Issue Date: | 18-Oct-2017 |
Publisher: | ACM |
Citation: | Vázquez-Ingelmo, A., Cruz-Benito, J., & García-Peñalvo, F. J. (2017). Improving the OEEU’s data-driven technological ecosystem’s interoperability with GraphQL. In J. M. Dodero, M. S. Ibarra Sáiz, & I. Ruiz Rube (Eds.), Fifth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM’17) (Cádiz, Spain, October 18-20, 2017) (Article 89). New York, NY, USA: ACM. doi:10.1145/3144826.3145437 |
Abstract: | A crucial part of data-driven ecosystems is the management and processing of complex data structures, as well as the proper handling of the data flows within the ecosystem. To manage these data flows, data-driven ecosystems need high levels of interoperability, as it allows the collaboration and independence of both internal and external components. REST APIs are a common solution to achieve interoperability, but sometimes they lack flexibility and performance. The arising of GraphQL APIs as a flexible, fast and stable protocol for data fetching makes it an interesting approach for data-intensive and complex data-driven (eco)systems. This paper outlines the GraphQL protocol and the benefits derived from its use, as well as it presents a case of study of the improvement experienced by the Observatory of Employment and Employability (also known as OEEU) ecosystem after including GraphQL as main API in several components. The results of the paper show promising improvements regarding the flexibility, maintainability and performance, among other benefits. |
URI: | http://repositorio.grial.eu/handle/grial/1063 |
ISBN: | 978-1-4503-5386-1 |
Appears in Collections: | Publications |
Files in This Item:
File | Description | Size | Format | |
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TEEM_2017_paper_89_preprint.pdf | Article | 2,45 MB | Adobe PDF | View/Open |
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