Assessing Quality Requirements for Onboarding Web Services to the European Open Science Cloud (EOSC): A Case Study of the Gaussian API
Date Issued
2023-12-14
Author(s)
Misheva, Despina
Stojcheva, Marija
Bosheva, Mia
Abstract
The European Open Science Cloud (EOSC) is an initiative by the European Commission to support
EU science by establishing a virtual environment for publishing, hosting, and reusing research. It
promotes common standards, interoperability, and best practices for sharing and utilizing data and
services. The EOSC platform contributes significantly to open science and facilitates transparent and
accessible knowledge sharing. The resource onboarding process to the EOSC requires compliance with the established quality criteria. This paper focuses on accessing quality criteria for successful onboarding, including a case study on the RESTful web service for fitting repulsive potentials in density-functional tight-binding with Gaussian process regression - Gaussian API. The onboarding process follows a sequential evaluation of a set of criteria. The examination of The Gaussian API integration into EOSC provides valuable insights into three main aspects: improving service quality, considering the benefits of Open Science, and addressing challenges related to the smooth onboarding process.
EU science by establishing a virtual environment for publishing, hosting, and reusing research. It
promotes common standards, interoperability, and best practices for sharing and utilizing data and
services. The EOSC platform contributes significantly to open science and facilitates transparent and
accessible knowledge sharing. The resource onboarding process to the EOSC requires compliance with the established quality criteria. This paper focuses on accessing quality criteria for successful onboarding, including a case study on the RESTful web service for fitting repulsive potentials in density-functional tight-binding with Gaussian process regression - Gaussian API. The onboarding process follows a sequential evaluation of a set of criteria. The examination of The Gaussian API integration into EOSC provides valuable insights into three main aspects: improving service quality, considering the benefits of Open Science, and addressing challenges related to the smooth onboarding process.
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