Programming scientific and distributed workflow with Triana services

By D. Churches, G. Gombás, A. Harrison, J. Maassen, Craig Robinson, Matthew S. Shields, Ian J. Taylor, I. Wang. Concurrency and Computation, 2006

326 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/d6702d9b06d4376d19babaa58d7e7b8b08a6b49e

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Citations in the corpus

• Provenance Collection Support in the Kepler Scientific Workflow System (2006, methodology): “Scientific workflow systems [1,2,3], aim to improve this situation by creating interfaces to a variety of technologies and providing tools with domain-independent customizable graphical user interfaces that combine different Cyberinfrastructure [4] technologies along with efficient methods for using”
• Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline (2009, unknown): “The Triana (Churches et al., 2006) workfl ow environment enables external data storage which signifi cantly improves the effi ciency and robustness of its user interface and optimizes the system requirements (e.g., low memory demands).”
• A data placement strategy in scientific cloud workflows (2010, unknown): “For examples, Kepler uses the SRB [26] system, while Pegasus [2] and Triana [27] adopt the RLS system [28], Gridbus [29] has a grid service broker [30] where all data are deemed as important resources.”