학술논문

DARE: A Reflective Platform Designed to Enable Agile Data-Driven Research on the Cloud
Document Type
Conference
Source
2019 15th International Conference on eScience (eScience) eScience (eScience), 2019 15th International Conference on. :578-585 Sep, 2019
Subject
Computing and Processing
software platform
cloud
technology
conceptualisation
data-driven science
scientific workflows
provenance
workflow optimization
Language
Abstract
The DARE platform has been designed to help research developers deliver user-facing applications and solutions over diverse underlying e-infrastructures, data and computational contexts. The platform is Cloud-ready, and relies on the exposure of APIs, which are suitable for raising the abstraction level and hiding complexity. At its core, the platform implements the cataloguing and execution of fine-grained and Python-based dispel4py workflows as services. Reflection is achieved via a logical knowledge base, comprising multiple internal catalogues, registries and semantics, while it supports persistent and pervasive data provenance. This paper presents design and implementation aspects of the DARE platform, as well as it provides directions for future development.