Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/13263
Authors: Klampanos, Iraklis* 
Davvetas, A* 
Gemund, André* 
Atkinson, Malcolm* 
Koukourikos, Antonis* 
Filgueira, Rosa* 
Krause, Amy* 
Spinuso, Alessandro* 
Charalambidis, Angelos* 
Magnoni, Federica* 
Casarotti, Emanuele* 
Pagé, Christian* 
Lindner, Mike* 
Karkaletsis, Vangelis* 
Title: DARE: A Reflective Platform Designed to Enable Agile Data-Driven Research on the Cloud
Issue Date: Sep-2019
DOI: 10.1109/eScience.2019.00079
Keywords: software platform
cloud
technology
conceptualization
data-driven science
scientific workflows
provenance
workflow optimization
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.
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